| WUSS |
2026 |
Demystifying Regression Analysis Techniques with R |
Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao |
|
35 |
| WUSS |
2026 |
Interactive Modeling with SAS Visual Statistics |
Danny R. Modlin |
source |
28 |
| PharmaSUG |
2026 |
Regression Analysis Made Easy Using R |
Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao |
source |
32 |
| PHUSE EU |
2025 |
Evaluating the Use of Real-World Data (RWD) as a Synthetic Control Group: A Statistical Approach |
Vasiliki Economou,
Dimitrios Kounelis |
source
poster source |
17 |
| MWSUG |
2025 |
Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source |
Jayanth Iyengar |
source |
32 |
| MWSUG |
2025 |
Large-Scale Time Series Forecasting in Model Studio |
Danny R. Modlin |
source |
39 |
| SESUG |
2025 |
Large-Scale Time Series Forecasting in Model Studio |
Danny R. Modlin |
|
39 |
| WUSS |
2025 |
Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source |
Jayanth Iyengar |
source |
32 |
| WUSS |
2025 |
Large-Scale Time Series Forecasting in Model Studio |
Danny R. Modlin |
source |
39 |
| PharmaSUG |
2025 |
Conducting Survival Analysis in SAS using Medicare Claims as a Real-world data source |
Jayanth Iyengar |
source |
32 |
| PharmaSUG |
2025 |
Practical Process in SAS of Using External Controls |
Hui Mao,
Na Wang,
Lixin Gao |
source |
5 |
| SESUG |
2024 |
A Comprehensive Analysis of the Relationship Between Depression, Sleep Deprivation, and Self-Esteem Using Advanced Statistical Methods |
Muslihat Adejoke Gaffari |
source |
43 |
| SESUG |
2024 |
Interactive Modeling with SAS Visual Statistics |
Danny R. Modlin |
source |
28 |
| WUSS |
2024 |
Analyzing Goalkeeper Impact in Premier League Football |
Alec Troy Christiansen,
Benjamin T Houser |
source |
10 |
| WUSS |
2024 |
Estimating causal effects of health interventions using instrumental variables |
Mehrnaz Siavoshi |
source |
7 |
| WUSS |
2024 |
Regression Analysis Made Easy Using SAS Studio |
Zheyuan (Walter) Yu |
source |
42 |
| PharmaSUG |
2024 |
Multiple Logistic Regression Analysis using Backward Selection Process on Objective Response Data with SAS |
Girish Kankipati,
Jai Deep Mittapalli |
source |
9 |
| PHUSE US |
2024 |
Analysis of Same Objective - Different SAS Procedures: How to Choose a SAS Procedure Wisely for a Statistical Analysis? |
Pradeep Acharya,
Ephicacy Lifescience |
source
presentation source |
9 |
| PHUSE US |
2024 |
Spline Analysis to Understand the Non-linear Relationship in Clinical Research |
Anwaya Joshi |
source
presentation source |
9 |
| WUSS |
2023 |
Leveraging Logistic Regression and Bootstrap Sampling to Assess a Decision Threshold in Classification Predictive Analytics |
Colleen E. McGahan |
source |
15 |
| WUSS |
2023 |
Regression Analysis Made Easy Using SAS Studio |
Kirk Paul Lafler,
Zheyuan (Walter) Yu,
Nuoer Lu,
Nicklas (Rebel) Yee,
Yanzhang Gavin Chen,
Kai Kang |
source |
43 |
| WUSS |
2023 |
Survey Data Analysis in SAS |
Denis Nyongesa,
Marianne Jurasic,
Gregg Gilbert,
Tamara Lischka |
source |
11 |
| SESUG |
2023 |
Longitudinal Analysis of Marital Therapy's Impact on Intimacy in Heterosexual Couples |
Yaa Awuah,
Mostafa Zahed |
source |
19 |
| SESUG |
2023 |
Performing Higher Education Enrollment Management Predictions Using SAS |
Phil Moore,
Marla Mamrick,
Sara Reinhardt |
source |
13 |
| SESUG |
2023 |
Regression Analysis Made Easy Using SAS Studio |
Kirk Paul Lafler,
Zheyuan (Walter) Yu,
Nuoer Lu,
Daniel Qian,
Kai Kang,
Yanzhang Gavin Chen,
Nicklas (Rebel) Yee,
Yixuan (Jason) Xiang |
source |
43 |
| SESUG |
2023 |
Systemic Quantitative check to identify if a variable is a confounder in a dataset using SAS Macro code |
Kannan Deivasigamani,
Douglas Lunsford |
source |
17 |
| PHUSE US |
2023 |
RBM and Failure Prediction Using Python for Health Monitoring Devices |
Vidya Muthukumar |
source
presentation source |
7 |
| SESUG |
2022 |
A Two-Staged Local Regression Based Binning Method for Weight of Evidence Transformation in Credit Scoring Models |
Hui Wang,
Shirong Huang,
Emma Zhou,
Erin Martin |
source |
30 |
| SESUG |
2022 |
Cutting Edge Regression Methods: Ridge, LASSO, LOESS, and GAM |
David J. Corliss |
source |
12 |
| SESUG |
2022 |
Use of JMP's Prediction Profiler to Predict Outcomes of Acute Spinal Cord Injury |
Melvin T. Alexander |
source |
9 |
| WUSS |
2022 |
Attribute Reduction for Continuous Dependent Variables in SAS |
Alec Zhixiao Lin |
source |
20 |
| WUSS |
2022 |
Should I Wear Pants in the Portuguese Expanse? Automating Business Rules and Decision Rules Through Reusable Decision Table Data Structures that Leverage SAS Arrays |
Troy Martin Hughes,
Louise S. Hadden |
source |
13 |
| PHUSE US |
2022 |
Machine Learning in R to Predict Outcomes from Biomarker Data [presentation] |
Benno F. Kurch,
Prakash Dev |
source
video |
21 |
| SESUG |
2021 |
Back to Basics: Running an Analysis from Data to Refinement in SAS |
Deanna Naomi Schreiber-Gregory |
source |
21 |
| SESUG |
2021 |
Using QUANTREG to Examine time and Drug on Histamine HA level in Mice |
Abbas S. Tavakoli,
Navid S. Tavakoli |
source |
7 |
| PHUSE US |
2021 |
Software Demonstration: SD14: Accelerate your Transition to R in 4 months: Learn About the Accel2R Accelerated Learning Program [presentation] |
Steve Walker |
source |
22 |
| PharmaSUG |
2021 |
Back to Basics: Running an Analysis from Data to Refinement in SAS |
Deanna Naomi Schreiber-Gregory |
source |
21 |
| PharmaSUG |
2021 |
Build a model: Introducing a methodology to develop multiple regression models using R in oncology trial analyses |
Girish Kankipati,
Jai Deep Mittapalli |
source |
20 |
| PharmaSUG |
2021 |
Mitigating Multicollinearity: Using Regulation Techniques to Minimize the Effect of Collinearity |
Deanna Naomi Schreiber-Gregory |
source |
23 |
| PharmaSUG |
2021 |
Should I Wear Pants in the Portuguese Expanse? Automating Business Rules and Decision Rules Through Reusable Decision Table Data Structures that Leverage SAS Arrays |
Troy Martin Hughes,
Louise S. Hadden |
source |
13 |
| PharmaSUG |
2021 |
Survival Statistics with PROC LIFETEST and PROC PHREG: Pitfall-Avoiding Survival Lessons for Programmers |
Yun (Julie) Zhuo |
source |
10 |
| SGF |
2021 |
Back to Basics: Running an Analysis from Data to Refinement in SAS |
Deanna Naomi Schreiber-Gregory |
source
presentation |
20 |
| SGF |
2021 |
Large-scale demand forecasting for e-commerce retailer using SAS Forecast Studio: A Case Study |
Ajay Kumar Mishra,
Mohak Narkhede,
Padmanabha Chandu Saladi |
source |
9 |
| SESUG |
2020 |
A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education |
Deanna Naomi Schreiber-Gregory |
source |
13 |
| SESUG |
2020 |
Using GENMOD to Calculate Prevalence Ratio for Concussion and Suicidal behaviors among U.S. High School Students |
Abbas S. Tavakoli |
source |
13 |
| SGF |
2020 |
%SURVEYCORRCOV Macro: Complex Survey Data Correlations for Multivariate Analysis and Model Building |
David R. Nelson,
Siew Wong-Jacobson |
source |
20 |
| SGF |
2020 |
A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education |
Deanna Naomi Schreiber-Gregory |
source |
13 |
| SGF |
2020 |
Add SGSCATTER, SGPLOT, SGPANEL and SGRENDER Procedures to Your SAS Toolbelt |
Alex Chaplin |
source |
16 |
| SGF |
2020 |
Analyzing Non-normal Data: Application to Missing Data Problems |
Niloofar Ramezani |
source |
10 |
| SGF |
2020 |
Analyzing the Factors Impacting Suicidal Behavior in American Youth |
Ashlesha Sampathi |
source |
7 |
| SGF |
2020 |
How to Build a Text Analytics Model in SAS Viya with Python |
Nate Gilmore |
source |
13 |
| SGF |
2020 |
Machine Learning Approach to Combat the Opioid Epidemic |
Navjot Kaur |
source |
15 |
| SGF |
2020 |
Multinomial vs. Ordinal. Does model selection make a difference? for SAS Global Forum 2020 |
Corey Leadbeater |
source |
15 |
| SGF |
2020 |
Neural-Network Based Forecasting Strategies in SAS Viya |
Steven C. Mills |
source |
14 |
| SGF |
2020 |
The New solveBlackbox Action in SAS Optimization 8.5 |
Edward P. Hughes |
source |
14 |
| SGF |
2020 |
The Seven Most Popular Machine Learning Algorithms for Online Fraud Detection and Their Use in SAS |
Patrick Maher |
source |
6 |
| SGF |
2020 |
Using Factor Analysis and MANOVA to Explore Academic Achievement in the 2016 Monitoring the Future Survey Data |
Stefanie Kairs |
source |
20 |
| SGF |
2020 |
Using SAS OpRisk Global Data to Improve Decision-Making at a Bank |
Mentje Gericke,
Helgard Raubenheimer |
source |
17 |
| SGF |
2020 |
Variable Selection Using Random Forests in SAS |
Denis Nyongesa |
source |
11 |
| SGF |
2020 |
You Are Using PROC GLM Too Much (and What You Should Be Using Instead) |
Peter L. Flom |
source |
22 |
| PharmaSUG |
2020 |
A Doctor's Dilemma: How Propensity Scores Can Help Control for Selection Bias in Medical Education |
Deanna Naomi Schreiber-Gregory |
source |
14 |
| PharmaSUG |
2020 |
RStats: A R-Shiny application for statistical analysis |
Sean Yang,
Hrideep Antony,
Aman Bahl |
source |
8 |
| PharmaSUG |
2020 |
Should I Wear Pants? And Where Should I Travel in the Portuguese Expanse? Automating Business Rules and Decision Rules Through Reusable Decision Table Data Structures |
Troy Martin Hughes,
Louise S. Hadden |
source |
13 |
| PharmaSUG |
2020 |
You Are Using PROC GLM Too Much (and What You Should Be Using Instead) |
Peter L. Flom,
Deanna Naomi Schreiber-Gregory |
source |
15 |
| PHUSE EU |
2019 |
SMART RPA - powered by Machine Learning |
Charan Kumar Kuyyamudira Janardhana |
source
presentation source |
10 |
| PHUSE EU |
2019 |
Symbolic Regression: Survival of the Best Fit |
Hector Leitch |
source
presentation source |
9 |
| SESUG |
2019 |
Advanced Statistical Modeling within Machine Learning and Big Data Analytics |
Niloofar Ramezani,
George Mason |
source |
16 |
| SESUG |
2019 |
Analyzing Airbnb reviews using SAS Text Miner and Predicting the factors contributing for higher ratings |
Ashlesha Sampathi |
source |
15 |
| SESUG |
2019 |
Glass Box Neural Networks |
Ross Bettinger |
source |
14 |
| SESUG |
2019 |
Should I Wear Pants? And Where Should I Travel in the Portuguese Expanse? Automating Business Rules and Decision Rules Through Reusable Decision Table Data Structures that Leverage SAS Arrays |
Troy Martin Hughes,
Louise S. Hadden |
source |
13 |
| SESUG |
2019 |
The Best of Both Worlds: Forecasting Using Time Series with Inputs |
David A. Dickey |
source |
19 |
| SESUG |
2019 |
The Thorn in My Side!! Logistic Regression Continuous Variables that Violate the Assumption of Linearity on the Log-odds (Logit) Scale: How to Identify and What to Do? |
Janet M. Grubber,
Cynthia J. Coffman |
source |
13 |
| MWSUG |
2019 |
Comparison of three methods for transforming predictor variables to improve model fit using SAS |
Douglas Thompson |
|
13 |
| MWSUG |
2019 |
Surviving Survival Analysis 101: Making the Likelihood Ratio Test Easier Using a Macro |
Katelyn Ware,
Rachel Baxter |
|
13 |
| WUSS |
2019 |
A strategy for speed Dating |
YuTing Tian |
source |
21 |
| WUSS |
2019 |
Choosing Wisely: Using the Appropriate Statistical Test for Trend in SAS |
Christina Park,
Jui-Ting Hsiung,
Melissa Soohoo,
Elani Streja |
source |
10 |
| WUSS |
2019 |
General, Age-Specific, and Total Fertility Rates in Montana, 2008-2017 |
Matthew Ringel |
source |
7 |
| WUSS |
2019 |
Ordinal vs. Multinomial: Does Model Selection Make a Difference? |
Corey Leadbeater |
source |
14 |
| WUSS |
2019 |
Polynomial Regression for Modeling Curvilinear Data: A Biological Example |
Elisha Johnston |
source |
20 |
| WUSS |
2019 |
PROC DTREE VS PROC HPSPLIT |
YuTing Tian |
source |
19 |
| WUSS |
2019 |
Variable Selection Using Random Forests in SAS |
Denis Nyongesa |
source |
11 |
| PharmaSUG |
2019 |
A SAS Macro to Provide Survival Functions along with Cox Regression Model Efficiently |
Chia-Ling (Ally) Wu |
source |
6 |
| PharmaSUG |
2019 |
Logistic and Linear Regression Assumptions: Violation Recognition and Control |
Deanna Naomi Schreiber-Gregory,
Karlen Bader |
source |
21 |
| PharmaSUG |
2019 |
Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets |
Deanna Naomi Schreiber-Gregory,
Karlen Bader |
source |
23 |
| PharmaSUG |
2019 |
SAS V9.4 MNAR statement for multiple imputations for missing not at random in longitudinal clinical trials |
Lingling Li |
source |
11 |
| SGF |
2019 |
A Selective Overview of Panel Data with Applications in SAS |
Oral Capps |
source |
26 |
| SGF |
2019 |
Analyzing Restricted Mean Survival Time Using SAS/STAT |
Changbin Guo,
So Ying |
source |
21 |
| SGF |
2019 |
Conducting Tests in Multivariate Regression |
Chii-Dean Joey Lin |
source |
13 |
| SGF |
2019 |
Developing a Credit Risk Model Using SAS |
Amos Odeleye |
source |
16 |
| SGF |
2019 |
Generating Sales Insights from Predictive Models |
Krzysztof Dzieciolowski |
source |
10 |
| SGF |
2019 |
Improve Your AML Monitoring While Reducing Costs with SAS Viya |
Calvin Crase,
Chris St. Jeor |
source |
11 |
| SGF |
2019 |
Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets |
Deanna Naomi Schreiber-Gregory |
source |
23 |
| SGF |
2019 |
Review and Comparing (Analyzing) Relationship between Teacher Judgment and Student Performance in North Carolina |
Sareh Meshkinfam,
Julie S. Ivy,
Amy C. Reamer |
source |
15 |
| SGF |
2019 |
SCORE! Techniques for Scoring Predictive Regression Models Using SAS/STAT Software |
Phil Gibbs,
Randy Tobias |
source |
18 |
| SGF |
2019 |
Screening, Transforming, and Fitting Predictors for the Cumulative Logit Model |
Bruce S. Lund |
source |
21 |
| SGF |
2019 |
The Best of Both Worlds: Forecasting Using Time Series with Inputs |
David A. Dickey |
source |
19 |
| SGF |
2019 |
Using SAS Forecast Server and the SASEFRED Engine to Enhance Your Forecast |
Catherine LaChapelle |
source |
7 |
| SGF |
2019 |
Writing a Gradient Boosting Model Node for SAS Visual Forecasting |
Yue Li,
Jingrui Xie,
Iman Vasheghani Farahani |
source |
19 |
| PHUSE US |
2019 |
Artificial Intelligence and Healthcare |
Aman Bahl,
Hrideep Antony |
source
presentation source |
10 |
| PHUSE US |
2019 |
Integrative Analysis of Circulating Tumor Cell Counts and Gene Expression Levels |
Yauheniya Cherkas |
source
presentation source |
8 |
| SCSUG |
2018 |
Deciphering cryptocurrencies: Sentiments and prices |
Priyansh Dadar |
source |
6 |
| PHUSE EU |
2018 |
Collinearity in Mixed Models |
John Hendrickx |
source
presentation source |
11 |
| PHUSE EU |
2018 |
Experiences and Strategies in Linking Real-world Data from Different Sources |
Berber Snoeijer |
source
presentation source |
6 |
| SESUG |
2018 |
Automated Comparison Tables using PROC REPORT |
Evan Kwiatkowski |
source |
6 |
| SESUG |
2018 |
Logistic and Linear Regression Assumptions: Violation Recognition and Control |
Deanna Naomi Schreiber-Gregory,
Henry M. Jackson |
source |
22 |
| SESUG |
2018 |
Predicting the Risk of Attrition for Undergraduate Students using SAS Enterprise Miner |
Sivateja Reddy Kandula |
source |
12 |
| SESUG |
2018 |
Predictive Modeling for Healthcare Professionals: The use of time-series analysis for health-related data and the application of ARIMA modeling techniques in SAS for Public Health Practice |
Camillia R. Comeaux |
source |
6 |
| SESUG |
2018 |
Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets |
Deanna Naomi Schreiber-Gregory,
Henry M. Jackson |
source |
23 |
| MWSUG |
2018 |
Alternative Methods of Regression when OLS is Not Right |
Peter L. Flom |
|
22 |
| MWSUG |
2018 |
Assessing Model Adequacy in Proportional Hazards Regression |
Michael G. Wilson |
|
37 |
| MWSUG |
2018 |
Logistic and Linear Regression Assumptions: Violation Recognition and Control |
Deanna Naomi Schreiber-Gregory,
Karlen Bader |
|
22 |
| MWSUG |
2018 |
Regularization Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets |
Deanna Naomi Schreiber-Gregory,
Karlen Bader |
|
23 |
| MWSUG |
2018 |
Screening, Transforming, and Fitting Predictors for Cumulative Logit Model |
Bruce S. Lund |
|
22 |
| WUSS |
2018 |
Logistic and Linear Regression Assumptions: Violation Recognition and Control |
Deanna Naomi Schreiber-Gregory |
source |
21 |
| WUSS |
2018 |
Regulation Techniques for Multicollinearity: Lasso, Ridge, and Elastic Nets |
Deanna Naomi Schreiber-Gregory |
source |
23 |
| PHUSE US |
2018 |
Feature Selection for Predictive Modelling - A Needle in a Haystack Problem |
Sudipta Basu |
source
presentation source |
6 |
| PharmaSUG |
2018 |
Multicollinearity: What Is It and What Can We Do About It? |
Deanna Naomi Schreiber-Gregory |
source |
13 |
| SGF |
2018 |
Alternative Variance Parameterizations in Count Data Models |
Robin High |
source |
14 |
| SGF |
2018 |
Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease Classification |
Jessica Rudd |
source |
10 |
| SGF |
2018 |
Claim Risk Scoring Using Survival Analysis Framework and Machine Learning with Random Forest |
Yuriy Chechulin |
source |
15 |
| SGF |
2018 |
Demystify Income Models with Advanced Machine Learning Techniques for Ultimate Accuracy |
Vickey Chang |
source |
18 |
| SGF |
2018 |
Distribution Circuit Load Forecasting Using Advanced Metering Infrastructure Data |
Prasenjit Shil,
Tom Anderson |
source |
12 |
| SGF |
2018 |
Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures |
Gerhard Svolba |
source |
26 |
| SGF |
2018 |
Getting Started with Survival Analysis |
Marc Huber |
source |
76 |
| SGF |
2018 |
Improved Campaigning at Africa's Largest Pay TV Service Provider with SAS Marketing Optimization |
Jean De Villiers |
source |
16 |
| SGF |
2018 |
Improving Game Strategies with Data Analytics: The Case of Euroleague Professional Basketball [presentation] |
Raha Akhavan-Tabatabaei,
Cem Yigman |
source |
35 |
| SGF |
2018 |
Insights into Using the GLIMMIX Procedure to Model Categorical Outcomes with Random Effects |
Kathleen Kiernan |
source |
23 |
| SGF |
2018 |
Location Matters: Evidence from Spatial Econometric Analysis of Opioid Prescription Rates |
Jonathan Mccopp |
source |
21 |
| SGF |
2018 |
Penalized Variable Selection and Quantile Regression in SAS : An Overview |
Russell M. Lavery |
source |
28 |
| SGF |
2018 |
Prediction and Interpretation for Machine Learning Regression Methods |
David Richard Cutler |
source |
16 |
| SGF |
2018 |
Robust Principal Component Analysis: Two Analyses in One |
Anthony Salis,
Zohreh Asgharzadeh,
Kyungduck Cha |
source |
11 |
| SGF |
2018 |
Role of Preventive Care and Lifestyle Changes in Chronic Diseases |
Asish Satpathy,
Satyajit Behari |
source |
13 |
| SGF |
2018 |
SAS Macros for Computing Causal Mediated Effects in Two- and Three-Wave Longitudinal Models |
David P. MacKinnon,
Matthew Valente |
source |
18 |
| SGF |
2018 |
SAS Visual Forecasting: A Cloud-Based Time Series Analysis and Forecasting System |
Jerzy M. Brzezicki,
Joseph H. Katz |
source |
21 |
| SESUG |
2017 |
Applying Logistics Regression to Forecast Annual Organizational Retirements |
Alan Dunham |
source |
12 |
| SESUG |
2017 |
Backward Variable Selection for Logistic Regression Based on Percentage Change in Odds Ratio |
Evan Kwiatkowski |
source |
6 |
| SESUG |
2017 |
Decomposing the R-squared of a Regression Using the Shapley Value in SAS |
Charles D. Coleman |
source |
11 |
| SESUG |
2017 |
Exploring JMP Modeling Functionality Using Consumer Expenditure Data |
Joshua Klick |
source |
12 |
| SESUG |
2017 |
Multicollinearity: What Is It, Why Should We Care, and How Can It Be Controlled? |
Deanna Naomi Schreiber-Gregory,
Henry M. Jackson |
source |
12 |
| SESUG |
2017 |
Using SAS to Employ Propensity Score Matching in an Institutional Research Office to Create Matched Groups for Outcomes Analyses |
Bobbie E. Frye,
James E. Bartlett |
source |
19 |
| PHUSE EU |
2017 |
The Model Statistician Insights into Model Selection Techniques in Clinical Trials |
Peter Williams |
source
presentation source |
6 |
| MWSUG |
2017 |
AIR Binder 2.0: A Dynamic Visualization, Data Analysis and Reporting SAS Application for Preclinical and Clinical ADME Assays, Pharmacokinetics, Metabolite Profiling and Identification |
Hao Sun,
Kristen Cardinal,
Richard Voorman |
|
26 |
| MWSUG |
2017 |
How Can an NBA Player Be Clutch?: A Logistic Regression Analysis |
Logan Edmonds |
|
18 |
| MWSUG |
2017 |
Logistic Model Selection with SAS PROC's LOGISTIC, HPLOGISTIC, HPGENSELECT |
Bruce S. Lund |
|
18 |
| MWSUG |
2017 |
Untangle Customer's Incrementality using Uplift Modeling with a Case Study on Direct Marketing Campaign |
Hairong Gu,
Yi Cao,
Chao Xu |
|
8 |
| WUSS |
2017 |
Five Things You Should Know about Quantile Regression |
Robert N. Rodriguez |
source |
19 |
| WUSS |
2017 |
Integrating Health Data Sources to Identify, Stratify, and Predict High Utilizers of Public Systems |
Benjamin Knisley,
Joshua Morgan,
Linn Carothers,
Keith Haigh |
source |
15 |
| WUSS |
2017 |
Multicollinearity: What Is It and What Can We Do About It? |
Deanna Naomi Schreiber-Gregory |
source |
12 |
| PharmaSUG |
2017 |
Multinomial Logistic Regression Models With Sas Proc Surveylogistic |
Marina Komaroff |
source |
7 |
| SGF |
2017 |
A Hadoop Journey along the SAS Road |
Sumit Sukhwani,
Krutharth Peravalli,
Amit Gautam |
source |
8 |
| SGF |
2017 |
A Practical Guide to Getting Started with Propensity Scores |
Thomas Gant |
source |
10 |
| SGF |
2017 |
Analyzing Correlated Data in SAS |
Niloofar Ramezani |
source |
13 |
| SGF |
2017 |
Continuous Predictors in Regression Analyses |
Ruth Croxford |
source |
12 |
| SGF |
2017 |
Developing a Predictive Model of Physician Attribution of Patient Satisfaction Surveys |
Ken Ferrell |
source |
5 |
| SGF |
2017 |
Fitting a Cumulative Logistic Regression |
Shana Kelly |
source |
5 |
| SGF |
2017 |
Fitting Complex Statistical Models with NLMIXED and MCMC Procedures |
Robin High |
source |
14 |
| SGF |
2017 |
Five Things You Should Know about Quantile Regression |
Robert N. Rodriguez,
Yonggang Yao |
source |
19 |
| SGF |
2017 |
I'm Normal, You're Normal, but Is Your Weather Normal? |
Kyle Wood,
Jason Wilson,
Bradley Lawson,
Rain Xie |
source |
5 |
| SGF |
2017 |
Multicollinearity: What Is It, Why Should We Care, and How Can It Be Controlled? |
Deanna Naomi Schreiber-Gregory |
source |
12 |
| SGF |
2017 |
N-Stage Machine Learning Analysis with the LUA Procedure Helps Solve Big Data Analysis Problems |
Ryo Kiguchi,
Eri Sakai,
Yoshitake Kitanishi,
Akio Tsuji |
source |
8 |
| SGF |
2017 |
Pricing a Self-Funded Health Plan by Applying Generalized Linear Models Using SAS Enterprise Guide |
Luiz Carlos Leao |
source |
20 |
| SGF |
2017 |
PROC LOGISTIC: Using New SAS 9.4 Features for Cumulative Logit Models with Partial Proportional Odds |
Paul Hilliard |
source
zip
pdf |
16 |
| SGF |
2017 |
Real AdaBoost: Boosting for Credit Scorecards and Similarity to WOE Logistic Regression |
Paul Edwards |
source |
12 |
| SGF |
2017 |
Revenue Score: Forecasting Credit Card Products with Zero Inflated Beta Regression and Gradient Boosting |
Marc Witarsa,
Paulo Di Cellio Dias |
source |
20 |
| SGF |
2017 |
SAS Macros for Computing the Mediated Effect in the Pretest-Posttest Control Group Design |
David P. MacKinnon |
source |
10 |
| SGF |
2017 |
The Three Amigos Factors: Determining Term Deposit Purchases: How a Bank Can Get Other People's Money |
Gina Colaianni,
Bogdan Gadidov,
Matthew Mitchell |
source |
59 |
| SGF |
2017 |
The Truth Is Out There: Leveraging Census Data Using PROC SURVEYLOGISTIC |
Richard Dirmyer |
source |
5 |
| SGF |
2017 |
Using the LOGISTIC or SURVEYLOGISTIC Procedure and Weighting of Public-Use Data in the Classroom |
Tyler C. Smith,
Besa Smith |
source |
9 |
| SGF |
2017 |
Visualizing Market Structure Using Brand Sentiments |
Praveen Kumar Kotekal,
Amit K Ghosh,
Goutam Chakraborty |
source |
9 |
| SGF |
2017 |
What Statisticians Should Know about Machine Learning |
David Richard Cutler |
source |
13 |
| SGF |
2017 |
Where Does Cleopatra Really Belong? An Analysis of Slot Machine Placement and Performance Using SAS |
Stephen Tam |
source |
12 |
| SCSUG |
2016 |
Ten Tips for Simulating Data with SAS |
Rick Wicklin |
source |
15 |
| SESUG |
2016 |
A Simple SAS Macro to Perform Blinder-Oaxaca Decomposition |
Taylor Lewis,
Stanislas Ezoua |
source |
8 |
| SESUG |
2016 |
Analyzing non-normal data with categorical response variables |
Niloofar Ramezani,
Allameh Tabataba'i |
source |
9 |
| SESUG |
2016 |
How is Healthcare Cost Data Distributed? Using Proc Univariate to Draw Conclusions about Millions of Different Customers |
Aran Canes |
source |
8 |
| SESUG |
2016 |
In the Pursuit of Balanced Groups: A SAS Macro for an Adaptive Randomization Test |
Tyler Hicks,
Jeffrey D. Kromrey |
source |
9 |
| SESUG |
2016 |
Patients with Morbid Obesity and Congestive Heart Failure Have Longer Operative Time and Room Time in Total Hip Arthroplasty |
Yubo Gao |
source |
5 |
| SESUG |
2016 |
Using Regression Splines in SAS STAT Procedures |
Jonas V. Bilenas,
Nish Herat |
source |
19 |
| MWSUG |
2016 |
A Demonstration of Various Models Used in a Key Driver Analysis |
Steven M. LaLonde |
|
17 |
| MWSUG |
2016 |
An Analysis of the Repetitiveness of Lyrics in Predicting a Song's Popularity |
Drew Doyle |
|
12 |
| MWSUG |
2016 |
An Animated Guide: Penalized variable selection techniques in SAS and Quantile Regression |
Russell M. Lavery,
Peter Flom |
|
24 |
| MWSUG |
2016 |
An Innovative Method of Customer Clustering |
Brian Borchers |
|
6 |
| MWSUG |
2016 |
Automating the Process of Generating Publication Quality Regression Tables through SAS Base Programming |
Ji Qi |
|
16 |
| MWSUG |
2016 |
Fitting a Cumulative Logistic Regression Model |
Shana Kelly |
|
4 |
| MWSUG |
2016 |
Fitting Complex Statistical Models with PROCs NLMIXED and MCMC |
Robin High |
|
16 |
| MWSUG |
2016 |
Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL |
Drew Doyle |
|
11 |
| MWSUG |
2016 |
To be two or not be two, that is a LOGISTIC question |
Robert G. Downer |
|
10 |
| MWSUG |
2016 |
Use Multi-Stage Model to Target the Most Valuable Customers |
Chao Xu,
Jing Ren,
Hongying Yang |
|
10 |
| WUSS |
2016 |
How to analyze correlated and longitudinal data? |
Niloofar Ramezani |
source |
8 |
| WUSS |
2016 |
Selection Bias: How Can Propensity Score Utilization Help Control For It? |
Deanna Naomi Schreiber-Gregory |
source |
13 |
| WUSS |
2016 |
Social Media, Anonymity, and Fraud: HP Forest Node in SAS Enterprise Miner |
Taylor K. Larkin,
Denise J. McManus |
source |
5 |
| PharmaSUG |
2016 |
Cox proportional hazards regression to model the risk of outcomes per double increase in a continuous explanatory variable |
Seungyoung Hwang |
source |
4 |
| PharmaSUG |
2016 |
Mixed Effects Models |
Yan Wang |
source |
7 |
| PharmaSUG |
2016 |
Unequalslopes: Making life easier when the proportional odds assumption fails |
Matthew J. Wiedel |
source |
11 |
| SGF |
2016 |
Analyzing Non-Normal Binomial and Categorical Response Variables under Varying Data Conditions |
Niloofar Ramezani |
source |
16 |
| SGF |
2016 |
Breakthroughs at Old Dominion Electric Cooperative with Energy Load Forecasting Innovation |
David Hamilton,
Steve Becker,
Emily Forney |
source |
19 |
| SGF |
2016 |
Building a Recommender System with SAS to Improve Cross-Selling for Online Retailers |
Miao Nie,
Shanshan Cong |
source
zip |
12 |
| SGF |
2016 |
Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! |
Delali Agbenyegah |
source |
7 |
| SGF |
2016 |
Correcting the Quasi-complete Separation Issue in Logistic Regression Models |
Xinghe Lu |
source |
10 |
| SGF |
2016 |
Customer Lifetime Value Modeling |
Vadim Pliner |
source
presentation |
4 |
| SGF |
2016 |
Do SAS High-Performance Statistics Procedures Really Perform Highly ? A Comparison of HP and Legacy Procedures |
Diep T. Nguyen,
Sean Joo,
Anh P. Kellermann,
Jeffrey D. Kromrey,
Jessica Montgomery,
Patricia Rodríguez de Gil,
Yan Wang |
source
presentation |
10 |
| SGF |
2016 |
Exploring the Factors That Impact Injury Severity Using Hierarchical Linear Modeling (HLM) |
Pradeep Bista |
source |
9 |
| SGF |
2016 |
Making Better Decisions about Risk Classification Using Decision Trees in SAS Visual Analytics |
Stephen M. Overton,
Ben Murphy |
source |
13 |
| SGF |
2016 |
Outlier Detection Using the Forward Search in SAS/IML Studio |
Jos Polfliet |
source
zip |
12 |
| SGF |
2016 |
Predicting Forest Fire Occurrence and Incremental Fire Rate Using SAS 9.4 and SAS Enterprise Miner 14.1 |
Quyen Nguyen |
source |
12 |
| SGF |
2016 |
Probability Density for Repeated Events |
Bruce S. Lund |
source |
16 |
| SGF |
2016 |
Quantitle Regression versus Ordinary Least Squares Regression |
Ruth Croxford |
source |
10 |
| SGF |
2016 |
Reducing and Screening Redundant Variables in Logistic Regression Models Using SAS/STAT Software and SAS Enterprise Miner |
Xinghe Lu |
source |
10 |
| SGF |
2016 |
Upgrade from ARIMA to ARIMAX to Improve Forecasting Accuracy of Nonlinear Time-Series: Create Your Own Exogenous Variables Using Wavelet Analysis |
Woranat Wongdhamma |
source |
16 |
| SGF |
2016 |
Using Propensity Score Analyses to Adjust for Selection Bias: A Study of Adolescent Mental Illness and Substance Use |
Deanna Naomi Schreiber-Gregory |
source |
7 |
| SCSUG |
2015 |
Using SAS Software to Determine the Mixed Rotterdam Demand Model Parameters and Test Statistical References |
Maryam Tabarestani,
Hector Zapata |
|
23 |
| MWSUG |
2015 |
A Macro for Systematic Treatment of Special Values in Weight of Evidence Variable Transformation |
Chaoxian Cai |
|
9 |
| MWSUG |
2015 |
Can You Stop the Guesswork in Your Marketing Budget Allocation? Marketing Mixed Modeling Using SAS Can Help! |
Delali Agbenyegah |
|
7 |
| MWSUG |
2015 |
Fitting and Evaluating Logistic Regression Models |
Bruce S. Lund |
|
26 |
| MWSUG |
2015 |
Get the highest bangs for your marketing bucks using Incremental Response Models in SAS Enterprise Miner |
Delali Agbenyegah |
|
8 |
| MWSUG |
2015 |
How to Build a Hierarchical Mixed Model in SAS |
Sara Burns,
Amit Amin,
Eric Novak |
|
8 |
| MWSUG |
2015 |
SAS Software as an Essential Tool in Statistical Consulting and Research |
Erika Larsen,
Timothy E. O'Brien |
|
13 |
| MWSUG |
2015 |
Utilizing Propensity Score Analyses to Adjust for Selection Bias: A Study of Adolescent Mental Illness and Substance Use |
Deanna Naomi Schreiber-Gregory |
|
7 |
| SESUG |
2015 |
Alternative Methods of Regression when OLS is Not Right |
Peter L. Flom |
source |
28 |
| SESUG |
2015 |
ANOVA_Robust: A SAS Macro for Various Robust Approaches to Testing Mean Differences in One-Factor ANOVA Models |
Thanh V. Pham,
Eun Sook Kim,
Diep T. Nguyen,
Yan Wang,
Jeffrey D. Kromrey,
Yi-Hsin Chen |
source |
14 |
| SESUG |
2015 |
High-Performance Procedures in SAS 9.4: Comparing Performance of HP and Legacy Procedures |
Jessica Montgomery,
Sean Joo,
Anh P. Kellermann,
Jeffrey D. Kromrey,
Diep T. Nguyen,
Patricia Rodríguez de Gil,
Yan Wang |
source |
10 |
| SESUG |
2015 |
Optimizing Pilot Connection Time Using PROC REG and PROC LOGISTIC |
Andrew Hummel,
Shevawn Christian |
source |
4 |
| SESUG |
2015 |
Probability Density for Repeated Events |
Bruce S. Lund |
source |
16 |
| SESUG |
2015 |
Regression Analysis of the Levels of Chlorine in the Public Water Supply in Orange County, FL |
Drew Doyle |
source |
10 |
| WUSS |
2015 |
Data Analyses in Multivariate Regression |
Chii-Dean Joey Lin |
source |
9 |
| WUSS |
2015 |
Generalized Estimating Equations for Depression Dose Regimes |
Karen Walker |
source |
8 |
| WUSS |
2015 |
Introduction to SAS Quantile Regression (PROC QuantSelect and PROC QuantReg ) |
Peter L. Flom |
source |
25 |
| PharmaSUG CN |
2015 |
Why Statistical Analysis Plan (SAP) should be comprehensive. |
Riddhi Merchant,
Ranjith Prayankotveettil |
|
6 |
| SGF |
2015 |
A Genetic Algorithm for Data Reduction |
Lisa Henley |
source
zip |
7 |
| SGF |
2015 |
A New Method of Using Polytomous Independent Variables with Many Levels for the Binary Outcome of Big Data Analysis |
John Gao,
Jesse Harriott,
Lisa Pimentel |
source |
7 |
| SGF |
2015 |
Addressing AML Regulatory Pressures by Creating Customer Risk Rating Models with Ordinal Logistic Regression |
Edwin Rivera,
Jim West |
source |
12 |
| SGF |
2015 |
Alternative Methods of Regression when OLS is Not Right |
Peter L. Flom |
source |
19 |
| SGF |
2015 |
An Innovative Method of Customer Clustering |
Brian Borchers,
Ashlie Ossege |
source |
6 |
| SGF |
2015 |
Applied Analytics in Festival Tourism: A Case Study of Intention-to-Revisit Prediction in an Annual Local Food Festival in Thailand |
Jongsawas Chongwatpol,
Thanathorn Vajirakachorn |
source |
13 |
| SGF |
2015 |
Entropy-Based Measures of Weight of Evidence and Information Value for Variable Reduction and Segmentation for Continuous Dependent Variables |
Alec Zhixiao Lin |
source |
27 |
| SGF |
2015 |
Experimental Approaches to Marketing and Pricing Research |
Max Friedauer,
Jason Greenfield,
Yuhan Jia,
Joseph Thurman |
source |
22 |
| SGF |
2015 |
Forecasting Vehicle Sharing Demand Using SAS Forecast Studio |
Kushal Kathed,
Goutam Chakraborty,
Ayush Priyadarshi |
source |
9 |
| SGF |
2015 |
GEN_OMEGA2: A SAS Macro for Computing the Generalized Omega-Squared Effect Size Associated with Analysis of Variance Models |
Anh P. Kellermann,
Yi-Hsin Chen,
Jeffrey D. Kromrey,
Thanh Pham,
Patrice Rasmussen,
Patricia Rodríguez de Gil,
Jeanine L. Romano |
source |
12 |
| SGF |
2015 |
Imputing Missing Data using SAS |
Christopher Yim |
source |
9 |
| SGF |
2015 |
Introduce a Linear Regression Model by Using the Variable Transformation Method [presentation] |
Nancy Hu |
source
zip |
12 |
| SGF |
2015 |
Killing Them with Kindness: Policies Not Based on Data Might Do More Harm Than Good |
Tuesdi Helbig,
Matthew Foraker |
source |
22 |
| SGF |
2015 |
Modeling to Improve the Customer Unit Target Selection for Inspections of Commercial Losses in the Brazilian Electric Sector: The case of CEMIG |
Sergio Henrique Ribeiro,
Iguatinan Monteiro |
source |
7 |
| SGF |
2015 |
Multilevel Models for Categorical Data Using SAS PROC GLIMMIX: The Basics |
Mihaela Ene,
Bethany A. Bell,
Genine L. Blue,
Elizabeth Leighton |
source |
12 |
| SGF |
2015 |
Multinomial Logistic Model for Long-Term Value |
Bruce S. Lund |
source |
16 |
| SGF |
2015 |
Predicting Transformer Lifetime Using Survival Analysis and Modeling Risk Associated with Overloaded Transformers Using SAS Enterprise Miner 12.1 |
Balamurugan Mohan,
Goutam Chakraborty |
source |
18 |
| SGF |
2015 |
Random vs. Fixed Effects: Which Technique More Effectively Addresses Selection Bias in Observational Studies |
Jessica Navratil-Strawn,
Stephen Hartley,
Ronald J. Ozminkowski |
source
zip |
8 |
| SGF |
2015 |
Reducing the Bias: Practical Application of Propensity Score Matching in Healthcare Program Evaluation |
Amber Schmitz,
Jessica Navratil-Strawn,
Stephen Hartley,
Ronald J. Ozminkowski |
source |
7 |
| SGF |
2015 |
Selection and Transformation of Continuous Predictors for Logistic Regression |
Bruce S. Lund |
source |
16 |
| SGF |
2015 |
Sensing Demand Signals and Shaping Future Demand Using Multi-tiered Causal Analysis |
Charlie Chase |
source |
8 |
| SGF |
2015 |
Sums of Squares: The Basics and a Surprise |
Sheila Barron,
Michelle Mengeling |
source |
8 |
| SGF |
2015 |
Ten Tips for Simulating Data with SAS |
Rick Wicklin |
source
zip |
15 |
| SGF |
2015 |
Time Series Modeling and Forecasting--An Application to Stress-Test Banks |
Ania Supady |
source |
13 |
| SGF |
2015 |
Working with Panel Data: Extracting Value from Multiple Customer Observations |
Bobby Gutierrez,
Kenneth Sanford |
source
zip |
10 |
| SCSUG |
2014 |
Building Better Credit Scores using Reject Inference and SAS |
Steve Fleming |
|
15 |
| SCSUG |
2014 |
Selection and Transformation of Continuous Predictors for Logistic Regression |
Bruce S. Lund |
|
13 |
| SESUG |
2014 |
%DISCIT Macro: Pre-screening continuous variables for subsequent binary logistic regression analysis through visualization |
Mohamed S. Anany |
source |
6 |
| SESUG |
2014 |
ANOVA_HOV: A SAS Macro for Testing Homogeneity of Variance in One-Factor ANOVA Models |
Diep T. Nguyen,
Thanh V. Pham,
Patricia Rodríguez de Gil,
Tyler Hicks,
Yan Wang,
Isaac Y. Li,
Aarti P. Bellara,
Jeanine L. Romano,
Eun Sook Kim,
Harold Holmes,
Yi-Hsin Chen,
Jeffrey D. Kromrey |
source |
12 |
| SESUG |
2014 |
Don't be binary! Tales of Non-binary Categorical Regression |
Charlotte Baker |
source |
6 |
| SESUG |
2014 |
Expanding the Use of Weight of Evidence and Information Value to Continuous Dependent Variables for Variable Reduction and Scorecard Development |
Alec Zhixiao Lin,
Tung-Ying Hsieh |
|
23 |
| SESUG |
2014 |
Identifying Superutilizers in the Medicaid Population - A Simple and Powerful technique |
Aran Canes |
|
7 |
| SESUG |
2014 |
Manage Variable Lists for Improved Readability and Modifiability |
David H. Abbott,
Veterans Affairs |
source |
4 |
| SESUG |
2014 |
Multilevel Models for Categorical Data Using SAS PROC GLIMMIX: The Basics |
Mihaela Ene,
Elizabeth A. Leighton,
Genine L. Blue,
Bethany A. Bell |
source |
12 |
| SESUG |
2014 |
Overview of Analysis of Covariance (ANCOVA) Using GLM in SAS |
Abbas S. Tavakoli |
source |
10 |
| SESUG |
2014 |
Using SAS to Examine Mediator, Direct and Indirect Effects of Isolation and Fear on Social Support Using Baron& Kenny Combined with Bootstrapping Methods |
Abbas S. Tavakoli,
Sue P. Heiney |
source |
12 |
| PHUSE EU |
2014 |
Conjoint Analysis of Treatment Preference |
Milena Balcerzak |
source
presentation source |
12 |
| MWSUG |
2014 |
Analyzing Collection Effectiveness using Incremental Response Modeling |
Ryan Burton |
|
7 |
| MWSUG |
2014 |
Creating an Easy to Use, Dynamic, Flexible Summary Table Macro with P-Values in SAS for Research Studies |
Amy Gravely,
Barbara Clothier,
Sean Nugent |
|
10 |
| MWSUG |
2014 |
Measuring Product-level Promotional Effectiveness using Multiple Linear Regression |
Aaron Clark,
Cory Weinmann,
Donald Kirk |
|
10 |
| MWSUG |
2014 |
Reducing the Bias: Practical Application of Propensity Score Matching in Healthcare Program Evaluation |
Amber Schmitz,
Jessica Navratil-Strawn,
Stephen Hartley,
Ronald J. Ozminkowski |
|
7 |
| MWSUG |
2014 |
Selection and Transformation of Continuous Predictors for Logistic Regression |
Bruce S. Lund |
|
12 |
| MWSUG |
2014 |
Should more of your PROC REGS be QUANTREGs and ROBUSTREGs? |
Peter L. Flom |
|
17 |
| WUSS |
2014 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna |
source |
16 |
| WUSS |
2014 |
Decision Trees as a Predictive Modeling Method |
Gerry Hobbs |
source |
8 |
| WUSS |
2014 |
Fuzzy Bootstrap Matching |
Dale Harrington |
source |
9 |
| PharmaSUG |
2014 |
%IC_LOGISTIC: A SAS Macro to Produce Sorted Information Criteria (AIC/BIC) List for PROC LOGISTIC for Model Selection |
Qinlei Huang,
Liang Zhu |
source |
12 |
| PharmaSUG |
2014 |
Survival Analysis Approaches and New Developments using SAS |
Jane Lu,
David Shen |
source |
13 |
| PharmaSUG |
2014 |
The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction |
Ashwini S Erande,
Shaista Malik |
source |
11 |
| PharmaSUG |
2014 |
Using SAS to Calculate and Compare Adjusted Relative Risks, Odds Ratios, and Hazard Ratios |
Besa Smith,
Tyler C. Smith |
source |
23 |
| SGF |
2014 |
A Stepwise Algorithm for Generalized Linear Mixed Models |
Nagaraj Neerchal,
Jorge Morel,
Xuang Huang,
Alain Moluh |
source |
11 |
| SGF |
2014 |
Association of Socio-Emotional Factors: Religious Affiliation, Depression to Suicidal Tendency Among Adolescent Girls |
Sesha Sai Ega,
Chandra Shekar Pulipati,
Venkata Rachapudi |
source |
6 |
| SGF |
2014 |
Healthcare Services Data Distribution, Transformation, and Model Fitting |
Dawit Mulugeta,
Jason Greenfield,
Tison Bolen,
Lisa Conley |
source |
22 |
| SGF |
2014 |
How Predictive Analytics Turns Mad Bulls into Predictable Animals |
Marcel Baumgartner |
source |
5 |
| SGF |
2014 |
Improving the Thermal Efficiency of Coal-Fired Power Plants: A Data Mining Approach |
Thanrawee Phurithititanapong,
Jongsawas Chongwatpol |
source |
12 |
| SGF |
2014 |
Intermittent Demand Forecasting and Multi-tiered Causal Analysis |
Edward Katz |
source |
11 |
| SGF |
2014 |
Leveraging Publicly Available Data in the Classroom Using SAS PROC SURVEYLOGISTIC |
Tyler C. Smith,
Besa Smith |
source |
18 |
| SGF |
2014 |
Measures of Fit for Logistic Regression |
Paul D. Allison |
source |
12 |
| SGF |
2014 |
Medical Scoring for Breast Cancer Recurrence |
Nurul Husna Jamian,
Yap Bee Wah,
Nor Aina Emran |
source |
13 |
| SGF |
2014 |
Nonnegative Least Squares Regression in SAS |
Matthew Duchnowski |
source |
5 |
| SGF |
2014 |
SAS for Bayesian Mediation Analysis |
Miočević Milica,
David P. MacKinnon |
source |
11 |
| SGF |
2014 |
Scatter Plot Smoothing Using PROC LOESS and Restricted Cubic Splines |
Jonas V. Bilenas |
source |
11 |
| SGF |
2014 |
Scenarios Where Utilizing a Spline Model in Developing a Regression Model Is Appropriate |
Ning Huang |
source |
9 |
| SGF |
2014 |
The Use of Analytics for Insurance Claim Fraud Detection: A Unique Challenge |
Roosevelt Mosley,
Nick Kucera |
source |
15 |
| SGF |
2014 |
Top Seven Techniques for Creating SAS Web Applications |
Yogendra Joshi |
source |
20 |
| SGF |
2014 |
Using SAS to Evaluate Patient-Directed Quality of Care Interventions |
Scott P. Leslie |
source |
10 |
| WUSS |
2013 |
A Tutorial on PROC LOGISTIC |
Arthur X. Li |
source |
19 |
| WUSS |
2013 |
An Algorithm for ARIMA Dynamic Regression Variable Selection |
Ross Bettinger |
source |
14 |
| WUSS |
2013 |
Decision Trees as a Predictive Modeling Method |
Gerry Hobbs |
source |
8 |
| WUSS |
2013 |
How to Compute Custom Hazard Ratio in SAS (V8.2&V9.2) PHREG Procedure |
Liguo Cheng,
Yu Li |
source |
8 |
| WUSS |
2013 |
The Association of Morbid Obesity with Mortality and Coronary Revascularization among Patients with Acute Myocardial Infarction using ARRAYS, PROC FREQ and PROC LOGISTIC" |
Ashwini Erande,
Shaista Malik |
source |
11 |
| WUSS |
2013 |
Tools for Imputing Missing Data |
Taylor Lewis |
source |
16 |
| SESUG |
2013 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna |
source |
16 |
| SESUG |
2013 |
Dealing with Missing Data for Credit Scoring |
Steve Fleming |
source |
7 |
| SESUG |
2013 |
Forecasting Enrollment in Higher Education using SAS Forecast Studio |
Forecasting Enrollment |
source |
5 |
| SESUG |
2013 |
GEN_OMEGA2: A SAS Macro for Computing the Generalized Omega-Squared Effect Size Associated with Analysis of Variance Models |
Squared Effect Size Associated |
source |
10 |
| SESUG |
2013 |
Introducing the New ADAPTIVEREG Procedure for Adaptive Regression |
Warren F,
Weijie Cai |
source |
21 |
| PHUSE EU |
2013 |
Generic Functions in R Illustrated by Examples for the Survival Package [presentation] |
Martin Gregory |
source |
24 |
| MWSUG |
2013 |
A Tutorial on PROC LOGISTIC |
Arthur X. Li |
|
19 |
| MWSUG |
2013 |
Improved Interaction Interpretation: Application of the EFFECTPLOT statement and other useful features in PROC LOGISTIC |
Robert G. Downer |
|
8 |
| MWSUG |
2013 |
Information Value Statistic |
Bruce S. Lund,
David Brotherton |
|
18 |
| MWSUG |
2013 |
Residential Energy Efficiency and the Principal-Agent Problem |
Ryan Anderson |
|
11 |
| MWSUG |
2013 |
SAS PROC REPORT: How It Helps Improving College Student Retention Rate |
Harjanto Djunaidi,
Monica Djunaidi |
|
14 |
| NESUG |
2013 |
Proc SurveyCorr |
Jessica R. Hampton |
|
7 |
| SGF |
2013 |
A Flexible Method to Apply Multiple Imputation Using SAS/IML Studio |
Lisa M. Lix,
Xue Yao |
source
pdf |
9 |
| SGF |
2013 |
A Flock of C-Stats, or Efficiently Computing Multiple Statistics for Hundreds of Variables |
Bruce S. Lund,
Steven Raimi |
source |
11 |
| SGF |
2013 |
A Multilevel Model Primer Using SAS PROC MIXED |
Bethany A. Bell,
Jason A. Schoeneberger,
Mihaela Ene,
Whitney Smiley |
source |
19 |
| SGF |
2013 |
A SAS Macro for Applying Multiple Imputation to Multilevel Data |
Stephen Mistler |
source |
8 |
| SGF |
2013 |
Assessing Model Adequacy in Proportional Hazards Regression |
Michael G. Wilson |
source |
36 |
| SGF |
2013 |
Cox Proportional Hazard Model Evaluation in One Shot |
Polina Kukhareva |
source |
11 |
| SGF |
2013 |
Data Merging and Visualization to Identify Associations Between Environmental Factors and Disease Outbreaks |
Azhar Nizam,
Neeta Shenvi,
Xin Zhang |
source |
12 |
| SGF |
2013 |
Examining Mediator and Indirect Effects of Loneliness in Social Support on Social Well-Being Using the Baron and Kenny Method and a Bootstrapping Method |
Abbas S. Tavakoli,
Sue P. Heiney |
source |
12 |
| SGF |
2013 |
GEN_ETA2: A SAS Macro for Computing the Generalized Eta-Squared Effect Size Associated with Analysis of Variance Models |
Anh P. Kellermann,
Jeanine L. Romano,
Jeffrey D. Kromrey,
Patrice Rasmussen,
Patricia Rodríguez de Gil,
Thanh Pham,
Yi-Hsin Chen |
source
pdf |
10 |
| SGF |
2013 |
Models for Ordinal Response Data |
Robin High |
source |
16 |
| SGF |
2013 |
Nontemporal ARIMA Models in Statistical Research |
David J. Corliss |
source |
10 |
| SGF |
2013 |
Quantile Regression in Pharmaceutical Marketing Research |
George Mu |
source |
4 |
| SGF |
2013 |
Regression of NASCAR: Looking into Five Years of Jimmie Johnson |
Alex Herrington,
Liuchun Yang,
Yun Gao |
source |
20 |
| SGF |
2013 |
Statistical Analyses Using SAS Enterprise Guide |
Scott P. Leslie |
source |
11 |
| SGF |
2013 |
The Value of Neighborhood Information in Prospect Selection Models: Investigating the Optimal Level of Granularity |
Dirk Van den Poel,
Philippe Baecke |
source |
15 |
| SGF |
2013 |
Using Data Mining in Forecasting Problems |
Chip Wells,
Justin Kauhl,
Timothy Rey |
source |
17 |
| SGF |
2013 |
Variance Partition: My Mission and Ambition Come to Fruition |
Brenda Beaty,
L. Miriam Dickinson |
source |
8 |
| NESUG |
2012 |
Efficiently Screening Predictor Variables for Logistic Models |
Steven Raimi,
Bruce S. Lund |
|
13 |
| NESUG |
2012 |
Generalized Additive Models in Marketing Mix Modeling Revisited |
Patralekha Bhattacharya |
|
9 |
| NESUG |
2012 |
Profiling Consumer Price Index Formulas |
Joshua Klick |
|
6 |
| NESUG |
2012 |
Scatter Plot Smoothing Using PROC LOESS and Restricted Cubic Splines |
Jonas V. Bilenas |
|
12 |
| NESUG |
2012 |
Target Trained Transformations for Predictive Modeling |
Talbot M. Katz |
|
9 |
| NESUG |
2012 |
Using SAS to Test, Probe and Display Interaction Effects in Regression |
Timothy Gravelle |
|
16 |
| SCSUG |
2012 |
Use and Applications of JMP in Microbial Ecology |
Jose Garcia-Mazcorro |
source |
17 |
| PHUSE EU |
2012 |
Estimating Terminal Half Life by Non-Compartmental Methods with Some Data Below the Limit of Quantification |
Jochen Müller-Cohrs |
source |
6 |
| PHUSE EU |
2012 |
Multicollinearity Diagnostics in Statistical Modeling and Remedies to Deal with it Using SAS |
Harshada Joshi,
Swapna Deshpande |
source
presentation source |
12 |
| PHUSE EU |
2012 |
Programming Challenges of Sampling Controls to Cases from the Dynamic Risk Sets in Nested Case Control Studies |
Victor Kiri |
source
presentation source |
8 |
| PHUSE EU |
2012 |
The Logic and Logistics of Logistic Regression, Including New Features in SAS 9.2 |
Lawrence Rasouliyan |
source
presentation source |
16 |
| SESUG |
2012 |
Data merging and Exploration to identify association of Epidemiological outbreaks with Environmental factors |
Neeta Shenvi,
Xin Zhang,
Azhar Nizam |
source |
16 |
| SESUG |
2012 |
Spatial Analysis of Gastric Cancer in Costa Rica using SAS Software |
So Young Park,
Marcela Alfaro-Cordoba |
source |
8 |
| SESUG |
2012 |
The Keouk County CAFO Study: A Complementary Analysis Using Classification Trees in SAS Enterprise Miner |
Leonard Gordon |
source |
8 |
| MWSUG |
2012 |
Collapsing Levels of Predictor Variables for Logistic Regression and Weight of Evidence Coding |
Bruce S. Lund,
Steven Raimi |
|
13 |
| MWSUG |
2012 |
Direct Marketing Profit Model |
Bruce S. Lund |
|
8 |
| MWSUG |
2012 |
Modeling Complex Survey Data |
Taylor Lewis |
|
16 |
| MWSUG |
2012 |
Models for Ordinal Response Data |
Robin High |
|
11 |
| WUSS |
2012 |
Analysis of Dietary Patterns over Freshman Year of College |
Chelsea Lofland |
source |
8 |
| WUSS |
2012 |
How Do Child Support Order Amounts Affect Payments and Compliance? |
Mark Takayesu |
source |
12 |
| WUSS |
2012 |
I Want to Get Married Too: Assessing the Relationship between Marital Status and Education for African American Women |
Shanetta Robinson,
Tara Jiles,
AnnMaria De Mars |
source |
11 |
| WUSS |
2012 |
The Steps to Follow in a Multiple Regression Analysis |
Theresa H. Ngo |
source |
12 |
| WUSS |
2012 |
Up To Speed With Categorical Data Analysis |
Maura E. Stokes |
source |
25 |
| PharmaSUG |
2012 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna,
Anurag Katare |
source |
16 |
| PharmaSUG |
2012 |
Algorithm to Compare the Slopes (Regression Coefficients) between the subgroups in Simple/Multiple Regression using PROC REG |
Sandeep Sawant |
source |
3 |
| SGF |
2012 |
A Hitchhiker's Guide for Performance Assessment and Benchmarking SAS Applications |
Viraj R Kumbhakarna,
Anurag Katare |
source |
17 |
| SGF |
2012 |
A SAS Macro for Computing Point Estimates and Confidence Intervals of Effect Sizes Associated with Mediation Analysis |
Merlande Petit-Bois,
Thanh V. Pham,
Eun Kyeng Baek,
Jeffrey D. Kromrey |
source |
12 |
| SGF |
2012 |
Analyzing the Time Series of U.S. E-Commerce Using PROC UCM |
Anders Milhøj |
source |
11 |
| SGF |
2012 |
Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables |
Eric P. Elkin |
source |
8 |
| SGF |
2012 |
Black Box PROCs: PROC LOGISTIC Discovered |
Isabel H. Perry |
source |
7 |
| SGF |
2012 |
Building WOE Binned LGD Scorecards using SAS Enterprise Miner |
Anthony J. van Berkel,
Naeem Siddiqi |
source |
14 |
| SGF |
2012 |
Constructing a Credit Risk Scorecard Using Predictive Clusters |
Andres F. Gonzalez,
Alejandro Correa Bahnsen,
Ana C. Nieto,
Darwin A. Amezquita |
source |
13 |
| SGF |
2012 |
CSI: Customer Segmentation Intelligence for Increasing Profits |
Darius S. Baer |
source |
13 |
| SGF |
2012 |
Handling Missing Data by Maximum Likelihood |
Paul D. Allison |
source |
21 |
| SGF |
2012 |
Including the Salesperson Effect in Purchasing Behavior Models Using PROC GLIMMIX |
Philippe Baecke,
Dirk Van den Poel |
source |
11 |
| SGF |
2012 |
Inflated Beta Regression: Zero, One, and Everything in Between |
Christopher J. Swearingen,
Maria S. Melguizo,
Zoran Bursac |
source |
11 |
| SGF |
2012 |
Introduction to Predictive Modeling with Examples |
David A. Dickey |
source |
14 |
| SGF |
2012 |
The Steps to Follow in a Multiple Regression Analysis |
Theresa H. Ngo |
source |
12 |
| SGF |
2012 |
Transforming Variables for Normality and Linearity - When, How, Why and Why Not's |
Steven M. LaLonde |
source |
8 |
| SGF |
2012 |
Using SAS to Extend Logistic Regression |
Dachao Liu |
source |
8 |
| SGF |
2012 |
Your Survival Guide to Using Time-Dependent Covariates |
Melissa E. Bagnell,
Teresa M. Powell |
source |
10 |
| SCSUG |
2011 |
An Introductory Look at the Situational Context Inherent in the RBI Using Two Modeling Approaches |
Ryan Sides |
source |
14 |
| SCSUG |
2011 |
Statistical comparison of relative proportions of bacterial genetic sequences |
Jose F Garcia-Mazcorro |
source |
19 |
| SCSUG |
2011 |
Using Proc Logistic, SAS Macros and ODS Output to evaluate the consistency of independent variables during the development of logistic regression models. An example from the retail banking industry |
Alexandros Vidras |
source |
9 |
| SESUG |
2011 |
Acknowledging the Unknown: A SAS Macro for Investigating Omitted Variable Bias in Two-Level Linear Models |
Jason A. Schoeneberger,
Bethany A. Bell,
Jeffrey D. Kromrey |
source |
16 |
| SESUG |
2011 |
An Exact Implicit Enumeration Algorithm for Variable Selection in Multiple Linear Regression Models Using Information Criteria |
Dennis J. Beal |
source |
12 |
| SESUG |
2011 |
Analysis of a Binary Outcome Variable Using the FREQ and LOGISTIC Procedures |
Arthur X. Li |
source |
18 |
| SESUG |
2011 |
CI_MEDIATE: A SAS Macro for Computing Point and Interval Estimates of Effect Sizes Associated with Mediation Analysis |
Thanh V. Pham,
Eun Kyeng Baek,
Merlande Petit-Bois,
Jeffrey D. Kromrey |
source |
10 |
| SESUG |
2011 |
Eyes on the Road: A Methodology for Analyzing Complex Eye-Tracking Data |
Eye Tracking |
source |
11 |
| SESUG |
2011 |
Tailoring Logistic Regression Model Analyses with the ODDSRATIO Statement in PROC LOGISTIC |
Taylor Lewis |
source |
8 |
| WUSS |
2011 |
Modeling Interactive Advertising on TiVo: Overcoming the Challenges of Collinearity, Efficiency and Practicality |
Rachel Poulsen |
source |
10 |
| WUSS |
2011 |
Principal Component Regression as a Countermeasure against Collinearity |
Chong Ho Yu |
source |
7 |
| WUSS |
2011 |
Up To Speed With Categorical Data Analysis |
Maura E. Stokes |
source |
25 |
| MWSUG |
2011 |
A Hitchhiker's guide for performance assessment & benchmarking SAS applications |
Viraj R Kumbhakarna,
Anurag Katare |
|
16 |
| MWSUG |
2011 |
Before Logistic Modeling - A Toolkit for Identifying and Transforming Relevant Predictors |
Steven Raimi,
Bruce S. Lund |
|
18 |
| MWSUG |
2011 |
Increased Life Expectancy from Positive Perceptions of Retirement |
Reuben Ng,
Deepak C. Lakra,
Becca R. Levy |
|
10 |
| MWSUG |
2011 |
SAS Model Selection Macros for Complex Survey Data Using PROC SURVEYLOGISTIC/SURVEYREG |
Fang Wang,
Hee-Choon Shin |
|
27 |
| MWSUG |
2011 |
Using SAS to Extend Logistic Regression |
Dachao Liu |
|
8 |
| NESUG |
2011 |
A Comparison of PDLREG and GAM Procedures in Measuring Dynamic Effects |
Patralekha Bhattacharya |
|
11 |
| NESUG |
2011 |
An Optimal Search Process of "Eigen Knots" for Spline Logistic Regression |
John Gao,
Cheryl Caswell |
|
7 |
| NESUG |
2011 |
Feature Selection and Dimension Reduction Techniques in SAS |
Sassoon Kosian,
Varun Aggarwal |
|
6 |
| PharmaSUG |
2011 |
Formulas Calculating Risk Estimates and Testing for Effect Modification and Confounding |
Manojkumar B Agravat |
source |
44 |
| SGF |
2011 |
A Match Made in Heaven: Predictive Analytics and the SAS BI Dashboard 4.3 |
Keith Renison |
source |
13 |
| SGF |
2011 |
An Application of SAS Simulation Studio: The Microsimulation of a Computer-Assisted Telephone Interviewing System |
Yves Belanger,
Kristen Couture,
Elisabeth Neusy |
source |
8 |
| SGF |
2011 |
BASE SAS Implementation of Information Theoretic Feature Selection for Neural Networks |
Martin B. Jetton |
source |
13 |
| SGF |
2011 |
Bivariate Count Data Regression Models: A SAS Macro Program |
Nan-Ting Chou,
David Steenhard |
source |
10 |
| SGF |
2011 |
Compare the Effectiveness of Different Methodologies in Prediction of Dichotomous Outcome |
Jimmy Fang |
source |
8 |
| SGF |
2011 |
Comparison of Imputation Methods to Examine Mediator Effect for Social Support of Mothers of Mentally Ill Children |
Abbas S. Tavakoli,
Kathleen Scharer,
James Hussey |
source |
7 |
| SGF |
2011 |
Modeling Percentage Outcomes: The %Beta_Regression Macro |
Christopher J. Swearingen,
Maria S. Melguizo,
Zoran Bursac |
source |
12 |
| SGF |
2011 |
Optimization of Gas-Injected Oil Wells |
Robert N. Hatton,
Ken M. Potter |
source |
11 |
| SGF |
2011 |
PROC PANEL Vs. A FAST ALGORITHM FOR ESTIMATION OF UNBALANCED PANEL DATA MODELS WITH TWO FIXED EFFECTS |
Alan Ricardo da Silva,
Mariana Fernandes Teixeira,
Thaís Helena Fernandes Teixeira |
source |
12 |
| SGF |
2011 |
Those Confounded Interactions: Building and Interpreting a Model with Many Potential Confounders and Interactions |
David J. Pasta |
source |
13 |
| SGF |
2011 |
To Hash or Not To Hash! That Is the Question!! When it Comes to SQL!!! |
Mustaq Ahmad |
source |
12 |
| SGF |
2011 |
Up To Speed With Categorical Data Analysis |
Gary G. Koch,
Maura E. Stokes |
source |
25 |
| NESUG |
2010 |
A Benchmarking Technique to Identify Best Practices in SAS |
Tony Pisegna |
|
14 |
| NESUG |
2010 |
An Exercise Using PROC SURVEYREG and NYC HANES: Examining Social Support as a Predictor of Body Mass Index in New York City |
Jackie Lee |
|
6 |
| NESUG |
2010 |
Improve Customer Retention by Answering Who and Why? |
Ward Thomas |
|
8 |
| NESUG |
2010 |
The Next Generation: SAS/STAT 9.22 |
Maura E. Stokes,
Robert N. Rodriguez,
Robert Cohen |
|
20 |
| NESUG |
2010 |
The Quest for Causation: An Introduction to Correlation and Regression Analysis |
Ian Stockwell |
|
9 |
| WUSS |
2010 |
101 Applications of Multivariate Statistical Procedures: PRINCOMP, CLUSTER, DISCRIM in SAS 9.2 |
Keh-Dong Shiang |
source |
22 |
| WUSS |
2010 |
Answering Your Research Questions with Inferential Statistics |
Diana D. Suhr |
source |
10 |
| WUSS |
2010 |
Data Visualization: "Every Picture Tells a Story" or "Putting Atomic Numbers on Your Socks"? |
AnnMaria De Mars |
source |
11 |
| WUSS |
2010 |
Decision Trees as a Predictive Modeling Method |
Gerry Hobbs |
source |
7 |
| WUSS |
2010 |
Dummy Coding for Dummies |
Kathryn Martin |
source |
10 |
| WUSS |
2010 |
The Next Generation: SAS/STAT 9.22 |
Robert N. Rodriguez |
source |
20 |
| WUSS |
2010 |
Those Confounded Interactions: Building and Interpreting a Model with Many Potential Confounders and Interactions |
David J. Pasta |
source |
9 |
| PHUSE EU |
2010 |
Useful Tips for Analysis of Variance (ANOVA) in Multicentre, Placebo Controlled Clinical Trials |
Joanna Romaniuk |
source
presentation source |
12 |
| MWSUG |
2010 |
PROC LIFEREG or PROC PHREG |
Dachao Liu |
|
9 |
| MWSUG |
2010 |
The Next Generation: SAS/STAT 9.22 |
Maura E. Stokes |
|
20 |
| MWSUG |
2010 |
Tips and Tricks: More SAS/GRAPH Map Secrets |
A. Darrell Massengill |
|
15 |
| MWSUG |
2010 |
Using SAS to Assess and Model Time-to-Event Data with Non-Proportional Hazards |
Michael G. Wilson |
|
24 |
| MWSUG |
2010 |
Visualization with JMP - The Overlay, Spinning, Surface, and Contour Plots |
Mark Anawis |
|
20 |
| SESUG |
2010 |
%SBSBOXPLOT: A SAS Macro for Generating Side-by-Side Boxplots |
Jason A. Schoeneberger,
Grant B. Morgan,
Bethany A. Bell |
source |
16 |
| SESUG |
2010 |
ES_ANOVA: A SAS Macro for Computing Point and Interval Estimates of Effect Sizes Associated with Analysis of Variance Models |
Jeffrey D. Kromrey,
Bethany A. Bell |
source |
10 |
| PharmaSUG |
2010 |
Surviving Survival Analysis: Basic Knowledge from a Programmer's Viewpoint |
Deb Cassidy |
|
9 |
| PharmaSUG |
2010 |
The Graph Template Language and the Statistical Graphics Procedures: An Example-Driven Introduction |
Warren F |
|
20 |
| SGF |
2010 |
An Analytical Approach to Determining Customer Value in the Property and Casualty Insurance Industry |
Roosevelt Mosley |
source |
20 |
| SGF |
2010 |
Dancing the Sample-Size Limbo with Mixed Models: How Low Can You Go? |
Bethany A. Bell,
Grant B. Morgan,
Jason A. Schoeneberger,
Brandon L. Loudermilk,
Jeffrey D. Kromrey,
John M. Ferron |
source |
11 |
| SGF |
2010 |
Getting Correct Results from PROC REG |
Nathaniel Derby |
source |
14 |
| SGF |
2010 |
The Graph Template Language and the Statistical Graphics Procedures: An Example-Driven Introduction |
Warren F. Kuhfeld |
source |
20 |
| SGF |
2010 |
Using Recycled Predictions for Computing Marginal Effects |
Zhongmin Li,
Geeta Mahendra |
source |
10 |
| SGF |
2010 |
Using the SAS System and SAS Enterprise Miner for Data Mining: A Study of Cancer Survival at the Mayo Clinic |
Leonard Gordon |
source |
6 |
| SESUG |
2009 |
A New Effect Modification P Value Test Demonstrated |
Manojkumar B Agravat |
source |
14 |
| SESUG |
2009 |
Getting Correct Results from PROC REG |
Nathaniel Derby |
source |
14 |
| SESUG |
2009 |
Tips and Tricks IV: More SAS/GRAPH Map Secrets |
A. Darrell Massengill,
Jeffrey C. Phillips |
source |
15 |
| SESUG |
2009 |
Using SAS to Explain Mediator and Moderator Effect for Social Support of Mothers of Mentally Ill Children |
Abbas S. Tavakoli |
source |
13 |
| MWSUG |
2009 |
Demonstration of Organic Growth Modeling for B to B Marketing |
Karen Ziton |
|
15 |
| MWSUG |
2009 |
Dietary Glycemic Load and Risk of Colon Cancer: A Guide to Data Management |
Svetlana Zelenskiy,
Lauren Byrne,
Cheryl L. Thompson,
Thomas C. Tucker,
David Bruckman,
Li Li |
|
16 |
| MWSUG |
2009 |
Getting Correct Results from PROC REG |
Nathaniel Derby |
|
14 |
| MWSUG |
2009 |
Mixed Model Selection |
George C. J. Fernandez |
|
19 |
| PNWSUG |
2009 |
Building Multiple Linear Regression Models - Food for Thought |
Colleen E. McGahan,
Mei Chong |
|
11 |
| PNWSUG |
2009 |
Getting Correct Results from PROC REG |
Nathaniel Derby |
|
14 |
| NESUG |
2009 |
The Application of Survival Analysis to Customer-Centric Forecasting |
Michael J. Berry |
|
10 |
| NESUG |
2009 |
What Drives Physicians to Use A Particular Product when Prescribing |
Marc States |
|
5 |
| WUSS |
2009 |
Automating the Process of Scoring a Generalized Linear Model Fitted using PROC GENMOD |
Prakash Gurumurthy |
source |
9 |
| WUSS |
2009 |
Discriminant Analysis, a Powerful Classification Technique in Predictive Modeling |
George C. J. Fernandez |
source |
20 |
| WUSS |
2009 |
Getting Correct Results from PROC REG |
Nathaniel Derby |
source |
14 |
| WUSS |
2009 |
Optimal Model Selection By a Genetic Algorithm Using SAS |
Jerry Tsai |
source |
13 |
| WUSS |
2009 |
Using PROC LOGISTIC to Estimate Willingness to Pay for Fresh Produce |
Mikael Peterson |
source |
4 |
| WUSS |
2009 |
Using Recycled Predictions for Estimating Marginal Effects |
Geeta Mahendra,
Zhongmin Li |
source |
9 |
| PharmaSUG |
2009 |
Illustrative Logistic Regression Examples using PROC LOGISTIC: New Features in SAS/STAT 9.2 |
Robert G. Downer,
Patrick J. Richardson |
|
11 |
| SGF |
2009 |
A Flexible Count Data Regression Model Using SAS PROC NLMIXED |
Nan-Ting Chou,
David Steenhard |
source |
14 |
| SGF |
2009 |
A SAS Macro for Adaptive Regression Modeling |
George J. Knafl |
source |
9 |
| SGF |
2009 |
An Analysis of Market Shares on the Danish Alcohol Market Using Unobserved Components |
Anders Milhøj |
source |
10 |
| SGF |
2009 |
Examining Mediator and Moderator Effect Using Rural-Women HIV Study |
Kirby Jackson,
Linda Moneyham,
Abbas S. Tavakoli |
source |
6 |
| SGF |
2009 |
Test Linearity between Continuous Confounder and Binary Outcome First, Run Multivariate Regression Analysis Second |
Jiming Fang,
Peter C. Austin,
Jack V. Tu |
source |
8 |
| SGF |
2009 |
The Problem of Regression Assumptions and the Use of Predictive Modeling |
Patricia B. Cerrito |
source |
20 |
| SGF |
2009 |
Tips and Techniques for Analytic Web Services |
Daniel Jahn,
Bradley W. Klenz |
source |
16 |
| SGF |
2009 |
Tips and Tricks IV: More SAS/GRAPH Map Secrets |
A. Darrell Massengill,
Jeffrey C. Phillips |
source
zip |
15 |
| WUSS |
2008 |
Comparing efficiency of cross validated partial least squares regression and ridge regression models in predicting spatial variability of total nitrogen concentration in Truckee River, Nevada. |
Anpalaki J. Ragavan |
source |
13 |
| WUSS |
2008 |
Evaluation of a Hospice Care Referral Program Using Cox Proportional Hazards Model |
Lida Gharibvand,
Daniel R. Jeske,
Solomon Liao |
source |
16 |
| WUSS |
2008 |
Score Test of Proportionality Assumption for Cox Models |
Xiao Chen |
source |
6 |
| WUSS |
2008 |
User-friendly SAS Macro Application for performing all possible mixed model selection - An update |
George C. J. Fernandez |
source |
19 |
| WUSS |
2008 |
Using Propensity Scores To Adjust For Treatment Selection Bias |
R. Scott Leslie |
source |
7 |
| SCSUG |
2008 |
Transaction Tracing |
Liang Xie |
|
7 |
| SESUG |
2008 |
Count Regression Models in SAS |
David Steenhard,
Nan-Ting Chou |
source |
12 |
| SESUG |
2008 |
Lithium Battery Analysis: Probability of Failure Assessment Using Logistic Regression |
Travis A. Moebes |
source |
9 |
| SESUG |
2008 |
Marketing Mix Modeling: Techniques and Challenges |
Patralekha Bhattacharya |
source |
6 |
| SESUG |
2008 |
Non Linear Programming Of Time Series Data To Minimize Eutrophication In Truckee River, Nevada |
Anpalaki J. Ragavan |
source |
13 |
| SESUG |
2008 |
SAS Code for Variable Selection in Multiple Linear Regression Models Using Information Criteria Methods with Explicit Enumeration for a Large Number of Independent Regressors |
Dennis J. Beal,
Oak Ridge |
source |
9 |
| SESUG |
2008 |
Techniques for Evidence-Based Decision Making Using SAS |
Ian Stockwell |
source |
8 |
| PHUSE EU |
2008 |
A Collection of SAS Macros to Calculate Odds Ratios using Spline Regression |
Martin Gregory |
source |
9 |
| PHUSE EU |
2008 |
Statistically guided review of safety data in clinical trials |
Michael O'Connell,
Harry Southworth |
source |
12 |
| PHUSE EU |
2008 |
Statistics for Non-Statisticians |
Shambhavi Nayak |
source |
10 |
| MWSUG |
2008 |
Classification of Breast Cancer Cells Using JMP |
Marie Gaudard |
|
34 |
| MWSUG |
2008 |
Inverse Prediction Using SAS Software: A Clinical Application |
Jayawant N. Mandrekar,
Cristine Allmer |
|
7 |
| MWSUG |
2008 |
Long-Term Value Modeling in the Automobile Industry |
Jeff Ames,
Cathy Hackett,
Bruce S. Lund |
|
6 |
| MWSUG |
2008 |
The Difference Between Predictive Modeling and Regression |
Patricia B. Cerrito |
|
19 |
| NESUG |
2008 |
Competing with Analytics: The Case of a College Bookstore |
Sunil Kumar Gupta |
|
14 |
| NESUG |
2008 |
Understanding Why Physicians Choose A Certain Drug When Treating A Patient - What Product Attributes Matter Most |
Marc States |
|
5 |
| PharmaSUG |
2008 |
Automated SAS Macro for Adverse Event Logistic Regression Analysis |
Suhas R. Sanjee |
|
8 |
| PharmaSUG |
2008 |
Bayesian Data Analysis Using %WinBUGS |
Lei Zhang |
|
18 |
| PharmaSUG |
2008 |
The Logic and Logistics of Logistic Regression |
Lawrence Rasouliyan,
Dave P. Miller |
|
14 |
| SGF |
2008 |
A SAS Text Mining Approach to Predicting the Resolvability of Disputes between eBays Sellers and Buyers |
Kevin S. Henning,
Zhangxi Lin |
source |
12 |
| SGF |
2008 |
Advanced Statistical and Graphical features of SAS PHREG |
Lida Gharibvand,
George C. J. Fernandez |
source |
12 |
| SGF |
2008 |
Adventures in ODS: Producing Customized Reports Using Output from Multiple SAS Procedures |
Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park |
source |
23 |
| SGF |
2008 |
Computational Algorithm for Estimation of Panel Data Models with Two Fixed Effects |
Alan Ricardo da Silva,
Patrick F. Alves |
source |
10 |
| SGF |
2008 |
Convergence Failures in Logistic Regression |
Paul D. Allison |
source |
11 |
| SGF |
2008 |
Count Data Models in SAS |
Wensui Liu,
Jimmy Cela |
source |
12 |
| SGF |
2008 |
Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis |
Anpalaki J. Ragavan |
source |
14 |
| SGF |
2008 |
How to Use SAS to Fit Multiple Logistic Regression Models |
Anpalaki J. Ragavan |
source |
13 |
| SGF |
2008 |
Integrating Consumer Demand to Improve Shipment Forecasts |
Charles Chase |
source |
10 |
| SGF |
2008 |
Introduction to Correlation and Regression Analysis |
Ian Stockwell |
source |
8 |
| SGF |
2008 |
Lithium Battery Analysis: Probability of Failure Assessment Using Logistic Regression |
Travis A. Moebes |
source |
9 |
| NESUG |
2007 |
Customizing Output for Regression Analyses Using ODS and the Data Step |
Zhenyi Xue |
|
11 |
| NESUG |
2007 |
PROC LOGISTIC: The Logistics Behind Interpreting Categorical Variable Effects |
Taylor Lewis |
|
7 |
| NESUG |
2007 |
Using Macro and ODS to Overcome Limitations of SAS Procedures |
Wei (Lisa) Lin,
Jing Su |
|
7 |
| NESUG |
2007 |
Using PROC GENMOD to Model Adverse Event Counts in a Healthcare Setting |
John Ulicny,
Thomas Klumpp |
|
13 |
| NESUG |
2007 |
Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology |
Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park |
|
22 |
| SESUG |
2007 |
Discrete Choice Modeling with PROC MDC |
John Ang |
source |
6 |
| SESUG |
2007 |
Information Criteria Methods in SAS for Multiple Linear Regression Models |
Dennis J. Beal |
source |
10 |
| SESUG |
2007 |
Integrating SAS and Microsoft .NET for Data Analysis |
Mai Nguyen,
Shane Trahan,
Patricia Nguyen,
Jonathan Cirella |
source |
10 |
| SESUG |
2007 |
Selection Bias Adjustment: Root Canal Therapy and Self-reported Oral Health |
Mark S. Litaker,
Sandre F. McNeal,
Gregg H. Gilbert |
source |
9 |
| WUSS |
2007 |
An Example of SAS Application in Public Health Research --- Predicting Smoking Behavior in Changqiao District, Shanghai, China |
Ding Ding |
source |
8 |
| WUSS |
2007 |
Automating Regression Analysis and PDF Report Output with the Use of Macros: Tricks for Disabling Default Delimiters and Making Use of Counters |
Svetlana Smorodinsky,
Bob McLaughlin |
source |
7 |
| WUSS |
2007 |
Health Outcomes Research Using Time-to-Event Analytic Approaches |
Tyler C. Smith,
Besa Smith |
source |
22 |
| WUSS |
2007 |
Time Series Cross Sectional Analysis of Total Nitrogen Concentration in Truckee River, Nevada Using SAS |
Anpalaki J. Ragavan |
source |
11 |
| WUSS |
2007 |
Using the NPAR1WAY Procedure to Investigate Philanthropy Preference Survey Data |
Joseph E. Earley,
Kimberly Rodriguez |
source |
7 |
| PharmaSUG |
2007 |
Effects of Multicollinearity in All Possible Mixed Model Selection |
George C. J. Fernandez |
|
18 |
| SGF |
2007 |
Effect Modification Investigation Using SAS - A Model-Building Exercise |
Vanessa Bundy,
Paule Barbeau,
Maribeth H. Johnson |
source |
11 |
| SGF |
2007 |
Model Selection in PROC MIXED-A User-Friendly SAS Macro Application |
George C. J. Fernandez |
source |
20 |
| SGF |
2007 |
OLS Regression? Auto-Regression? Dynamic Regression? |
Rodger Zhang |
source |
12 |
| SGF |
2007 |
Predicting Software Maintenance Outcomes Using Data Mining and Text Mining |
Uzma Raja |
source |
9 |
| SGF |
2007 |
SAS Macros for Automated Model Selection When the Response Variable Is Nominal-Needs and Solutions Involving PROC CATMOD |
Bonnie E. Williams,
Todd Kegan |
source |
12 |
| SGF |
2007 |
Saving Trees with Output Delivery System (ODS) |
Angelina D. Diehl,
Nancy Mandrekar,
Jayawant N. Tan |
source |
9 |
| SGF |
2007 |
Skewness, Multicollinearity, Heteroskedasticity - You Name It, Cost Data Have It! Solutions to Violations of Assumptions of the Ordinary Least Squares Regression Model Using SAS |
Leonor L. Ayyangar |
source |
7 |
| SGF |
2007 |
Using SAS Macros to Produce Tables for Publication from SAS-Callable SUDAAN |
Roger P. Pickering |
source |
10 |
| SGF |
2007 |
Variable Screening for Multinomial Logistic Regression on Very Large Data Sets as Applied to Direct Response Modeling |
John A. Cherrie |
source |
12 |
| MWSUG |
2006 |
A SAS Macro for Performing Backward Selection in Proc Surveyreg |
Qixuan Chen |
|
5 |
| MWSUG |
2006 |
All Possible Model Selection in Proc Mixed - A SAS macro application |
George C. J. Fernandez |
|
19 |
| PHUSE EU |
2006 |
Is your output telling you the truth? Tips and Tricks in verifying SAS Outputs |
Angelo Tinazzi,
Sonia Colombini |
source |
7 |
| SESUG |
2006 |
Combining PROC GENMOD Models with Multinomial Outcomes Using PROC MIANALYZE |
Marie Gantz |
source |
7 |
| SESUG |
2006 |
Creating RTF Tables with Univariate Analyses of Multiply Imputed Data |
Marie Gantz |
source |
14 |
| SESUG |
2006 |
Effect Modification Investigation Using SAS - A Model Building Exercise |
Vanessa Bundy,
Paule Barbeau,
Maribeth H. Johnson |
source |
10 |
| SESUG |
2006 |
Gene Expression Profiling of DNA Microarray Data using Association rule and Structural Equation Modeling |
Mussie A. Tesfamicael |
source |
7 |
| SESUG |
2006 |
Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures into a Single Summary Report, a Detailed Methodology |
Stuart D. Long |
source |
21 |
| WUSS |
2006 |
Detecting Structural Change Using SAS ETS Procedures |
Archie J. Calise,
Joseph E. Earley |
source |
7 |
| WUSS |
2006 |
Environmental Samples Below the Limits of Detection - Comparing Regression Methods to Predict Environmental Concentrations |
Daniel Smith,
Elana Silver,
Martha Harnly |
source |
8 |
| WUSS |
2006 |
Find the Best Prospects for a New Product by Using a Data Mining Model |
Ting Wu |
source |
8 |
| WUSS |
2006 |
Get the Correct Hazard Ratio from SAS PROC PHREG Procedure |
Betty Ying Wang |
source |
7 |
| WUSS |
2006 |
Model Selection Methods in PROC MIXED |
George C. J. Fernandez |
source |
19 |
| WUSS |
2006 |
PROC GENMOD with GEE to Analyze Correlated Outcomes Data Using SAS |
Tyler C. Smith,
Besa Smith |
source |
14 |
| WUSS |
2006 |
Skewness, Multicollinearity, Heteroskedasticity - You Name It, Cost Data Have It! Solutions to Violations of Assumptions of Ordinary Least Squares Regression Model Using SAS |
Leonor Ayyangar |
source |
7 |
| WUSS |
2006 |
The Logic and Logistics of Logistic Regression |
Lawrence Rasouliyan,
Dave P. Miller |
source |
14 |
| NESUG |
2006 |
Data Analysis: Beyond the Basics |
Ian Stockwell |
|
9 |
| NESUG |
2006 |
Logistic Regression Basics |
Joseph J. Guido,
Paul Winters,
Adam Rains |
|
7 |
| NESUG |
2006 |
Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 |
Jodi Blomberg,
Jacqueline K. Long |
|
12 |
| NESUG |
2006 |
Survey Logistic Regression: Some SAS-SUDAAN Comparisons |
Xiuhua Chen |
|
7 |
| NESUG |
2006 |
Using PROC GENMOD to Model Adverse Event Counts in a Healthcare Setting |
John Ulicny,
Thomas Klumpp |
|
13 |
| PharmaSUG |
2006 |
Heuristic Algo: Backwards Elimination Process for a Model |
Varsha C. Shah |
|
7 |
| SUGI |
2006 |
A Comparison of the MIXED Procedure and the GLIMMIX Procedure |
Jennifer L. Ferrell |
source |
8 |
| SUGI |
2006 |
An Evaluation of Splines in Linear Regression |
Deborah M. Hurley,
James Hussey,
Robert McKeown,
Cheryl L. Addy |
source |
11 |
| SUGI |
2006 |
Combining the Power of ODS, Data Set Concatenation, and DDE to Output Customized Statistical Results from SAS to Microsoft Excel |
Navneet K. Dhand,
Jenny-Ann Toribio |
source |
10 |
| SUGI |
2006 |
Fixed Effects Regression Methods in SAS |
Paul D. Allison |
source |
20 |
| SUGI |
2006 |
Introduction to SAS Enterprise Guide 4.1 for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
source |
22 |
| SUGI |
2006 |
Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 |
Jodi Blomberg,
Jacqueline K. Long |
source |
12 |
| SUGI |
2006 |
The Enigma of Survey Data Analysis: Comparison of SAS Survey Procedures and SUDAAN Procedures |
Katherine L. Baisden,
Paul Hu |
source |
11 |
| SUGI |
2006 |
Using SAS for Statistical Modeling of Nutrient Removal and Water Quality Aspects from Constructed Wetlands |
Rupali Mohansingh,
George C. J. Fernandez,
Keith E. Dennett |
source |
11 |
| SUGI |
2006 |
Using SAS ODS to Extract and Merge Statistics from Multiple SAS Procedures |
Stuart D. Long,
Jeffrey M. Abolafia,
Lawrence Park |
source |
21 |
| SUGI |
2006 |
Using SAS to Investigate Effect Modification |
Peter H. Van Ness,
Heather G. Allore |
source |
10 |
| SESUG |
2005 |
SAS Code to Select the Best Multiple Linear Regression Model for Multivariate Data Using Information Criteria |
Dennis J. Beal,
Oak Ridge |
source |
6 |
| MWSUG |
2005 |
Calculation Of Health Disparity Indices Using Data Mining And The SAS Bridge To ESRI |
Mussie A. Tesfamicael |
|
9 |
| MWSUG |
2005 |
Medicare Cost Estimation For Heart Disease |
Fariba Nowrouzi |
|
11 |
| WUSS |
2005 |
A Comparison of Two Procedures to Fit Multi-Level Data: PROC GLM versus PROC MIXED |
MaryAnne DePesquo Hope |
source |
7 |
| WUSS |
2005 |
A Journey to Ellis Island: Profiling Historical Immigration Using SAS and JMP Time Series Methods |
Archie J. Calise,
Joseph E. Earley |
source |
6 |
| WUSS |
2005 |
Graphing the Probability of Event as a Function of Time Using Survivor Function Estimates and the SAS System's PROC PHREG |
Tyler C. Smith,
Besa Smith |
source |
18 |
| NESUG |
2005 |
Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
|
20 |
| NESUG |
2005 |
Transforming Variables for Normality and Linearity - When, How, Why and Why Not's |
Steven M. LaLonde |
|
8 |
| PharmaSUG |
2005 |
Generating Customized Analytical Reports from SAS Procedure Output |
Brinda Bhaskar,
Kennan Murray |
|
9 |
| SUGI |
2005 |
A Comparison of Two Procedures to Fit Multi-Level Data: PROC GLM versus PROC MIXED |
Erin D. Shannon,
MaryAnne DePesquo Hope |
source |
7 |
| SUGI |
2005 |
Automating Predictive Analysis to Predict Medicare Fraud |
Christine L. Warner |
source |
9 |
| SUGI |
2005 |
Introducing SAS Forecast Studio |
Michael J. Leonard,
Brenda Wolfe,
Paddy Fahey |
source |
16 |
| SUGI |
2005 |
Introduction to SAS Enterprise Guide 3.0 for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
source |
20 |
| SUGI |
2005 |
Model Building in PROC PHREG with Automatic Variable Selection and Information Criteria |
Emily M. Cain,
Ken Kleinman,
Ernest S. Shtatland |
source |
10 |
| SUGI |
2005 |
Single Event Timing Model with Heterogeneity: Predicting the Time of the First Home Purchase by Immigrants |
Eugene Brusilovskiy |
source |
9 |
| SUGI |
2005 |
Teaching Data Mining in a University Environment |
David A. Dickey |
source |
11 |
| NESUG |
2004 |
A Regression Primer with a Touch of SAS |
Vincent Maffei |
|
14 |
| NESUG |
2004 |
An Animated Guide: Proc UCM |
Russell M. Lavery |
|
23 |
| NESUG |
2004 |
Generating Customized Analytical Reports from SAS Procedure Output |
Brinda Bhaskar,
Kennan Murray |
|
12 |
| NESUG |
2004 |
Introduction to Using Enterprise Guide for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
|
19 |
| SESUG |
2004 |
Binary Logistic Regression Model Optimization |
Jerry Musial |
source |
6 |
| SESUG |
2004 |
Structural Equation Modeling Assessing Micro Array Data |
Mussie A. Tesfamicael |
source |
10 |
| WUSS |
2004 |
A SAS Recent Analysis of the Us Stock Market Performance |
Kamal Shoukry |
source |
6 |
| WUSS |
2004 |
Beyond Binary Outcomes: PROC LOGISTIC to Model Ordinal and Nominal Dependent Variables |
Eric P. Elkin |
source |
8 |
| WUSS |
2004 |
Kaplan Meier And Cox Proportional Hazards Modeling: Hands On Survival Analysis |
Tyler C. Smith,
Besa Smith |
source |
14 |
| WUSS |
2004 |
Package, Archive, Report and Test Statistical Models Using ODS |
Ted Clay |
source |
10 |
| WUSS |
2004 |
PROC GENMOD for Analysis of Correlated Outcome Data Using the LOGIT Link Function |
Tyler C. Smith,
Besa Smith,
William Honner,
Ming Ji |
source |
14 |
| WUSS |
2004 |
The Continuing Quandary of Survey Data Part II:Comparison of SAS Procedures and SUDAAN Procedures |
Katherine L. Baisden |
source |
20 |
| MWSUG |
2004 |
Presenting the Binary Logit Model Effectively using SAS |
Hun Myoung Park |
|
11 |
| PharmaSUG |
2004 |
Traditional Repeated Measures Analysis Versus Random Coefficients Models Using PROC MIXED |
Radhi Abdulnabi |
|
9 |
| PharmaSUG |
2004 |
Using PROC LOESS With Sparse Data |
Kenneth S. Liu,
Alison Kellock |
|
7 |
| SUGI |
2004 |
An Introduction to Matching and Its Application Using the SAS System |
Jayawant N. Mandrekar,
Sumithra J. Mandrekar |
source |
9 |
| SUGI |
2004 |
Assessing Model Fit and Finding a Fit Model |
Margaret L. Bogle,
Rajiv Goel,
Robert M. Hamer,
Chan-Hee Jo,
Eric Siegel,
Pippa M. Simpson |
source |
17 |
| SUGI |
2004 |
Fitting Longitudinal Mixed Effect Logistic Regression Models with the NLMIXED Procedure |
Peter H. Van Ness,
John R. O'Leary,
Amy L. Byers,
Terri R. Fried,
Joel A. Dubin |
source |
7 |
| SUGI |
2004 |
Introduction to Using SAS Enterprise Guide for Statistical Analysis |
Charles B. Hallahan,
Linda P. Atkinson |
source |
20 |
| SUGI |
2004 |
Message Queue-Based Scoring Interface |
David R. Duling,
Robert Chu |
source |
6 |
| SUGI |
2004 |
Model-Based Multiple Imputation |
Geoffrey Paulin,
Shirley Tsai,
Melissa Grance |
source |
13 |
| SUGI |
2004 |
Some Statistical Strategies for Analyzing Confirmatory Studies Involving One or More Occurrences of Primary Events |
Gary G. Koch,
Maura E. Stokes |
source |
21 |
| WUSS |
2003 |
A SAS Macro Solution for Scoring Test Data with Output Features and Parameters from Logistic Regression Model Training |
Joseph Blue |
source |
5 |
| WUSS |
2003 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
6 |
| WUSS |
2003 |
Multiple Linear Regression Analysis of Percent of Students Taking the ACTs in Nevada High Schools |
Ramya R. Fernandez,
George C. J. Fernandez |
source |
6 |
| WUSS |
2003 |
Presenting Logistic Regression Models to Non-Statisticians: Adjusted Probabilities and Adjusted Risk Ratios |
David J. Pasta,
Miriam G. Cisternas |
source |
4 |
| WUSS |
2003 |
Regression Diagnostic Plots |
George C. J. Fernandez |
source |
9 |
| WUSS |
2003 |
Using SAS IN Educational Research |
Leping Liu |
source |
6 |
| SESUG |
2003 |
A Hybrid Modeling Platform to meet Basel II Requirements in Banking |
Jeffery Morrision |
source |
8 |
| SESUG |
2003 |
Bulletproofing and Knowledge Encapsulation in Statistical Macros |
John K. Troxell |
source |
4 |
| SESUG |
2003 |
Charting Your Course: Charts and Graphs for IT Projects |
Dawn Li,
Gary M. McQuown |
source |
9 |
| SESUG |
2003 |
Too Many Choices! The IMPORTANCE of Rank-Ordering Independent Variables Prior to Exploratory Data Analysis |
Gregg Weldon |
source |
5 |
| NESUG |
2003 |
Backwards Manual Selection (%bms): A Macro for Selecting Logistic Regression Models to Address Epidemiological Research Questions |
Janice Hegewald,
Anette Pfahlberg,
Wolfgang Uter |
|
5 |
| NESUG |
2003 |
Basic Usage of SAS/ETS' & SAS/STAT' to Forecast Time Series |
Douglas L. McAllaster |
|
10 |
| NESUG |
2003 |
Statistics & Regression - Easier than SAS |
Vincent Maffei,
Michael L. Davis |
|
6 |
| SEUGI |
2003 |
Putting Price Tags on Houses - Survival Analysis with Real Estate Data [presentation] |
Marco Salvi |
source |
18 |
| PharmaSUG |
2003 |
Using SAS Software and Visual Basic for Applications to Produce Microsoft Graph Charts |
Lori S. Parsons |
|
10 |
| SUGI |
2003 |
An Approach to Displaying Predicted Survival Data Based on the Level of a Continuous Covariate |
Cristine Allmer,
Daniel J. Sargent |
source |
4 |
| SUGI |
2003 |
Estimating Standard Errors for CLASS Variables in Generalized Linear Models Using PROC IML |
David J. Pasta,
Miriam G. Cisternas |
source |
6 |
| SUGI |
2003 |
Estimation of Prevalence Ratios When PROC GENMOD Does Not Converge |
James A. Deddens,
Martin R. Petersen,
Xiudong Lei |
source |
6 |
| SUGI |
2003 |
Fast and Easy Ways to Annoy a SAS Programmer: A Statistician's Revenge! |
Richard M. Mitchell |
source |
10 |
| SUGI |
2003 |
Logistic Regression Modeling - JMP StartTM Your Analysis with a Tree |
Pippa M. Simpson,
Renée A. Hall,
James G. Parker,
Jeffrey M. Gossett |
source |
5 |
| SUGI |
2003 |
SAS Macros and Tools for Working with Weighted Logistic Regression Models That Use Survey Data |
David Izrael,
Annabella A. Battaglia,
David C. Hoaglin,
Michael P. Battaglia |
source |
10 |
| SUGI |
2003 |
STEPWISE Methods in Using SAS PROC LOGISTIC and SAS Enterprise MinerTM for Prediction |
Ernest S. Shtatland,
Ken Kleinman,
Emily M. Cain |
source |
6 |
| SUGI |
2003 |
Survival Analysis Using Cox Proportional Hazards Modeling for Single and Multiple Event Time Data |
Tyler C. Smith,
Besa Smith,
Margaret A. K. Ryan |
source |
8 |
| SUGI |
2003 |
The Use of Geographic Information Systems to Investigate Environmental Pollutants in Relationship to Medical Treatment |
Patricia B. Cerrito,
Robert Forbes,
George R. Barnes |
source |
6 |
| SUGI |
2003 |
Using SAS Software and Visual Basic for Applications to Produce Microsoft Graph Charts |
Lori S. Parsons |
source |
10 |
| MWSUG |
2002 |
A Macro to Assess the Key Drivers of Overall Product Acceptance using SAS System |
George J. Hurley,
David Hengehold |
|
7 |
| MWSUG |
2002 |
JMP Density Ellipse Script Code Made Easy |
Charles E. Shipp,
Kirk Paul Lafler |
|
2 |
| MWSUG |
2002 |
JMP Density Ellipses for Pharmaceutical Analysis |
Charles E. Shipp,
Kirk Paul Lafler |
|
5 |
| SCSUG |
2002 |
Graphing in SAS Software |
Dana Rafiee |
|
18 |
| SCSUG |
2002 |
Using SAS to Generate JavaScript for Dynamic Web Pages |
Jim Hoffman |
|
3 |
| SCSUG |
2002 |
Web Enable Your Graphs and Reports |
Jessica Bonow |
|
11 |
| NESUG |
2002 |
"Easy and Fast, or Not?" |
Ming H. Chow |
|
6 |
| NESUG |
2002 |
Practice of SAS Logistic Regression on Binary Pharmacodynamic Data - Problems and Solutions |
Alan Xiao |
|
5 |
| SESUG |
2002 |
Analysis of Dosage-Response Data in Agricultural Research |
K. Bondari |
source |
6 |
| SESUG |
2002 |
Basic Usage of SAS/ETS Software to Forecast a Time Series |
Douglas L. McAllaster |
source |
10 |
| SESUG |
2002 |
JMP Density Ellipse Script Code Made Easy |
Charles E. Shipp,
Kirk Paul Lafler |
source |
2 |
| SESUG |
2002 |
JMP Density Ellipses for Pharmaceutical Analysis |
Charles E. Shipp,
Kirk Paul Lafler |
source |
5 |
| SESUG |
2002 |
The Lag-o-Matic: An Improved Method for Selecting the Lag Structure of Multiple Predictor Variables in the Absence of Theory |
David C. Sharp,
Stephen M. Finnigan |
source |
5 |
| WUSS |
2002 |
A Randomization-Test Wrapper for SAS PROCs |
Christopher F. Ake,
David L. Cassell |
source |
4 |
| WUSS |
2002 |
JMP Density Ellipse Script Code Made Easy |
Charles E. Shipp,
Kirk Paul Lafler |
source |
6 |
| WUSS |
2002 |
JMP Density Ellipses for Pharmaceutical Analysis |
Charles E. Shipp,
Kirk Paul Lafler |
source |
5 |
| WUSS |
2002 |
Multiple Linear Regression Analysis of Total Mercury Levels in Blood and Urine Samples |
Miki Yamauchi,
George C. J. Fernandez,
Stanley Omaye |
source |
6 |
| WUSS |
2002 |
Structural Equation Modeling: Easy Solutions Using SAS |
Shuqiang Zhang |
source |
5 |
| SEUGI |
2002 |
Customer management from a data warehouse - A Journey not a Destination [presentation] |
Tal Shlasky |
source |
33 |
| PharmaSUG |
2002 |
Bulletproofing and Knowledge Encapsulation in Statistical Macros |
John K. Troxell |
|
4 |
| PharmaSUG |
2002 |
Java Application Development for Analyzing Clinical Pharmacogenomics Data |
Zongwei Shen,
Robert Tracy,
Richard Judson |
|
4 |
| PharmaSUG |
2002 |
JMP Density Ellipses for Pharmaceutical Analysis |
Charles E. Shipp |
|
6 |
| PharmaSUG |
2002 |
Macros for Model Building, Summarizing, and Displaying Results of Stepwise Logistic Regressions |
Lori S. Parsons |
|
6 |
| PharmaSUG |
2002 |
Performing Logistic Regression on Survey Data with the New SURVEYLOGISTIC Procedure |
Anthony B. An |
|
10 |
| SUGI |
2002 |
A Proportional Odds/Hazards Approach to Analyzing Likert Scale Data |
Lynette K. Duncan,
James E. Dunn |
source |
5 |
| SUGI |
2002 |
A Randomization-Test Wrapper for SAS PROCs |
David L. Cassell |
source |
4 |
| SUGI |
2002 |
Communicating the Results of Predictive Models to Non-technical Audiences |
Andrew H. Karp |
source |
4 |
| SUGI |
2002 |
Fast and Easy Ways to Annoy a SAS Programmer: A Statistician's Revenge! |
Richard M. Mitchell |
source |
10 |
| SUGI |
2002 |
JMP Density Ellipses for Pharmaceutical Analysis |
Charles E. Shipp,
Kirk Paul Lafler |
source |
5 |
| SUGI |
2002 |
Macros for Model Building, Summarizing, and Displaying Results of Stepwise Logistic Regressions |
Lori S. Parsons |
source |
6 |
| SUGI |
2002 |
Performing Logistic Regression on Survey Data with the New SURVEYLOGISTIC Procedure |
Anthony B. An |
source |
9 |
| SUGI |
2002 |
Redesigning Experiments with Polychotomous Logistic Regression: A Power Computation Application |
Charles M. Vaughan,
Serge Guzy |
source |
6 |
| SUGI |
2002 |
SEM for Health, Business, and Education |
Diana D. Suhr |
source |
8 |
| SUGI |
2002 |
Use of the ROC Curve and the Bootstrap in Comparing Weighted Logistic Regression Models |
David Izrael,
Annabella Battaglia,
David C. Hoaglin,
Michael P. Battaglia |
source |
6 |
| SUGI |
2002 |
Using SAS Enterprise Miner for Data Quality Monitoring in the Veterans Health Administration's External Peer Review Program |
James H. Forsythe |
source |
5 |
| MWSUG |
2001 |
Modeling Lifetime Value in the Insurance Industry |
C. Olivia Parr Rud |
|
9 |
| NESUG |
2001 |
A Simple SAS Macro Technique to Build a Report Data Set |
Christianna S. Williams |
|
2 |
| NESUG |
2001 |
Applying Categorical Data Analysis to Multi-way Contingency Table-Location, Accident Type, and Related Factors With Severity. |
Li wan Chen |
|
10 |
| NESUG |
2001 |
Power and Sample Size Determination for Linear Models |
John M. Castelloe |
|
13 |
| NESUG |
2001 |
Untangling Correlated Predictors with Principle Components |
David R. Roberts |
|
5 |
| VIEWS |
2001 |
A Conjoint-based Choice Modelling Approach Using the PHREG Procedure to Evaluate the Importance of Fisheries Management Objectives |
Premachandra Wattage,
Simon Mardle,
Sean Pascoe |
|
14 |
| WUSS |
2001 |
A Survival Analysis from the Ground Up, Using Cox Proportional Hazards Modeling |
Tyler C. Smith,
Besa Smith,
Margaret A. K. Ryan |
source |
8 |
| WUSS |
2001 |
Estimating and Interpreting Ordered Regression Models using PROC PRINT |
Kenneth Fernandez |
source |
5 |
| WUSS |
2001 |
Gold, Black Gold, Steel, and World Inflation: A SAS Study |
Kamal Shoukry |
source |
3 |
| WUSS |
2001 |
Sinking the Big Hole: Using SAS/IntrNet Application Dispatcher Version 8 Features to Drill Down to the Depths of Your Data |
Thomas Kunselman |
source |
6 |
| WUSS |
2001 |
Using SAS to Assess Students' Learning in Instructional Technology Courses |
Leping Liu |
source |
6 |
| SESUG |
2001 |
GETTING STARTED WITH PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SESUG |
2001 |
Graphing in SAS Software |
Destiny Corporation (a company) |
source |
18 |
| SESUG |
2001 |
Heel Ultrasound As a Predictor of Appendicular Bone Mineral Density |
Rebecca G. Frederick,
Baton Rouge |
source |
5 |
| SESUG |
2001 |
Power and Sample Size Determination for Linear Models |
John M. Castelloe |
source |
13 |
| SCSUG |
2001 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SCSUG |
2001 |
Graphing in SAS Software |
Destiny Corporation (a company) |
|
18 |
| SCSUG |
2001 |
Heel Ultrasound As a Predictor of Appendicular Bone Mineral Density |
Rebecca G. Frederick,
E. Barry Moser,
Ellen R. Brooks |
|
5 |
| SCSUG |
2001 |
Power and Sample Size Determination for Linear Models |
John M. Castelloe,
Ralph G. O'Brien |
|
13 |
| PharmaSUG |
2001 |
Fitting Generalized Additive Models with the GAM Procedure |
Dong Xiang |
|
8 |
| SUGI |
2001 |
A Macro Program for ANOVA or ANCOVA, Using PROC GLM or PROC MIXED |
Zaizai Lu,
David Shen |
source |
4 |
| SUGI |
2001 |
A Non-mathematical Introduction to Regression Concepts Using PROC REG |
Mel Widawski |
source |
7 |
| SUGI |
2001 |
Fitting Generalized Additive Models with the GAM Procedure |
Dong Xiang |
source |
8 |
| SUGI |
2001 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SUGI |
2001 |
Model Fitting in PROC GENMOD |
Jean G. Orelien |
source |
6 |
| SUGI |
2001 |
Modeling Lifetime Value in the Insurance Industry |
C. Olivia Parr Rud |
source |
8 |
| SUGI |
2001 |
Outliers, Inliers, and Just Plain Liars - New Graphical EDA+ Techniques For Understanding Data |
Dave L. DesJardins |
source |
6 |
| SUGI |
2001 |
Survival Analysis and the Application of Cox's Proportional Hazards Modeling Using SAS |
Tyler C. Smith,
Besa Smith |
source |
9 |
| SCSUG |
2000 |
The Use of PROC MIXED for Analyzing Cohort-Sequential Designs |
C. Nathan Marti |
|
11 |
| SESUG |
2000 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
7 |
| SESUG |
2000 |
Macros In Scoring |
Jukui Yi |
source |
6 |
| SESUG |
2000 |
Using Data Mining Technology to Identify and Prioritize Emerging Opportunities for Mortgage Lending to Homeownership-Deficient Communities |
Mortgage Lending |
source |
10 |
| NESUG |
2000 |
Confirmatory and Exploratory Data Analyses Using PROC GENMOD: Factors Associated with Red Light Running Crashes |
Li wan Chen |
|
7 |
| NESUG |
2000 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| NESUG |
2000 |
How to Be a Bayesian in SAS: Model Selection Uncertainty in PROC LOGISTIC and PROC GENMOD |
Ernest S. Shtatland |
|
9 |
| NESUG |
2000 |
NPV Modeling for Direct Mail Insurance |
C. Olivia Parr Rud |
|
7 |
| NESUG |
2000 |
Point & Click Forecasting with the Time Series Forecasting System |
Charles B. Hallahan |
|
9 |
| WUSS |
2000 |
A Non-mathematical Introduction to Regression Using PROC REG |
Mel Widawski |
source |
6 |
| WUSS |
2000 |
A SAS Analysis of Social and Economic Well-Being: A MultCountry Cross-Section Longevity Study |
Seid M. Zekavat |
source |
5 |
| WUSS |
2000 |
An Overview of remedial tools for collinearity in SAS |
Chong Ho Yu |
source |
6 |
| WUSS |
2000 |
Analyzing Multiple Health Outcomes Using the SAS System's PROC CATMOD |
Besa Smith |
source |
5 |
| WUSS |
2000 |
Data Warehousing for Data Mining: A Case Study |
C. Olivia Parr Rud |
source |
9 |
| WUSS |
2000 |
Detecting Curvillnear Relationships in PROC REG |
Mel Widawski |
source |
9 |
| WUSS |
2000 |
Gaining Insight Using Visualization Techniques |
Curtis A. Smith,
Philip A. Cosby |
source |
5 |
| WUSS |
2000 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| WUSS |
2000 |
Graphing the Probability of Hospitalization as a Function of Time Using Estimates and the SAS System's PROC PHREG |
Tyler C. Smith |
source |
7 |
| WUSS |
2000 |
SAS STAT applications in Econometrics |
Mathura Thillainathan,
George C. J. Fernandez |
source |
10 |
| WUSS |
2000 |
Unemployment and the Money Supply: Estimating Lag Coefficients Using PROC PDLREG |
Jia L. Wang |
source |
6 |
| SEUGI |
2000 |
Forecasting Bad Debt by ARIMA Models with Multiple Transfer Functions using a Selection Process for many Candidate Variables [presentation] |
Alastair Jones,
Derek Hull,
John Adam |
source |
18 |
| SEUGI |
2000 |
SAS Software for the Analysis of Epidemiologic Data [presentation] |
Hans-Peter Altenburg |
source |
39 |
| PharmaSUG |
2000 |
Visualize Your Regression Analysis |
Fan Xu |
|
7 |
| SUGI |
2000 |
Calculating the Probability of Hospitalization as a Function of Time, An Application of Cox's Proportional Hazards Modeling |
Tyler C. Smith |
source |
5 |
| SUGI |
2000 |
Correcting for Missing Discrete Responses in Business Surveys |
Lawrence C. Marsh |
source |
10 |
| SUGI |
2000 |
Data Warehousing for Data Mining: A Case Study |
C. Olivia Parr Rud |
source |
9 |
| SUGI |
2000 |
Detecting Curvilinear Relationships in PROC REG |
Mel Widawski |
source |
9 |
| SUGI |
2000 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SUGI |
2000 |
Improved Confidence Interval on the Mean Response in Simple Linearizable Regression |
Mark Carpenter,
Pandu P. Kulkarni |
source |
6 |
| SUGI |
2000 |
Linear and Non-linear Modeling of a Dose-Response |
Sofia Paul |
source |
4 |
| SUGI |
2000 |
The Time Series Forecasting System |
Charles B. Hallahan |
source |
9 |
| SUGI |
2000 |
Using SAS Software to Perform a Case-Control Match on Propensity Score in an Observational Study |
Lori S. Parsons |
source |
6 |
| SESUG |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
7 |
| SESUG |
1999 |
Forecasting Army Officer Attrition with Logistic Regression Using The SAS System |
Douglas L. McAllaster |
source |
10 |
| SESUG |
1999 |
Utilizing SAS Software in the Evaluation of Virginia Tech's Academic Eligibility Policy |
Kristen H. Bush |
source |
6 |
| WUSS |
1999 |
A Logistic Regression on the Qualities of Educational Research: Characteristics of Publishable Articles |
Leping Liu,
George C. J. Fernandez |
source |
5 |
| WUSS |
1999 |
Calculating the Probability of Hospitalization as a Function of Time Using the SAS System's PROC PHREG |
Tyler C. Smith |
source |
5 |
| WUSS |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
6 |
| WUSS |
1999 |
Modeling Individual Utility Functions Using SAS PROC LOGISTIC: A Case Study Using the NES Data Set |
Godofredo Gatus |
source |
4 |
| WUSS |
1999 |
Polychotomous Logistic Regression and the Creation of Odds Ratios and Confidence Intervals Using the SAS PROC CATMOD |
Besa Nushi |
source |
5 |
| NESUG |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
7 |
| NESUG |
1999 |
Modeling Customer Choice |
David R. Roberts |
|
6 |
| MWSUG |
1999 |
REG, GLM, ANOVA: Which One? Why? How? |
Linda M. Quinn |
|
6 |
| MWSUG |
1999 |
Using Logistic Regression to Predict Customer Retention |
Andrew H. Karp |
|
5 |
| SEUGI |
1999 |
Comparison of various statistical techniques to support market retention and acquisition programs [presentation] |
Ian Thornhill |
source |
66 |
| SEUGI |
1999 |
Using SAS/IML to fit embedded models to accelerated life test data |
Alan John Watkins,
Richard E. Johnson |
source |
7 |
| SUGI |
1999 |
A SAS Macro to Analyze Data from a Matched or Finely Stratified Case-Control Design |
Robert A. Vierkant,
Terry M. Therneau,
Jon L. Kosanke,
James M. Naessens |
source |
6 |
| SUGI |
1999 |
Data Mining: An Overview of Methods and Techniques for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
7 |
| SUGI |
1999 |
Poisson Regression Adjustment of Event Rates and Its Macro Procedure ADJ_POIS |
Dingyi Zhao |
source |
6 |
| SUGI |
1999 |
Simplification on Learning Model by Using PROC GENMOD |
Kuolung Hu,
David Mckinzie,
Karen Nowak |
source |
6 |
| SUGI |
1999 |
The Time Series Forecasting System |
Charles B. Hallahan,
Renee Samy |
source |
9 |
| SUGI |
1999 |
Using SAS/INSIGHT Software as an Exploratory Data Mining Platform |
Robin Way |
source |
6 |
| MWSUG |
1998 |
An Introduction to Binary Logistic Regression |
Linda M. Quinn |
|
8 |
| MWSUG |
1998 |
If There Is A Will, There Is A Way: Getting Around Defaults of PROC LOGISTIC |
Chao-Ying Joanne Peng,
Tak-Shing Harry So |
|
10 |
| WUSS |
1998 |
Data Warehouses and Bayesian Analysis - A Match Made by SAS |
Ram Gopalan |
source |
6 |
| WUSS |
1998 |
Estimating Standard Errors of Treatment Effects for Probit Models and for Linear Models of Log-Transformed Variables with PROC IML |
David J. Pasta,
Miriam Cisternas,
Cynthia L. Williamson |
source |
6 |
| WUSS |
1998 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| WUSS |
1998 |
Multiple Regression and Model Selection on Developing a Computer Achievement Model |
Leping Liu,
George C. J. Fernandez |
source |
6 |
| WUSS |
1998 |
New SAS Procedures for Analysis of Sample Survey Data |
Anthony B. An,
Donna L. Watts |
source |
11 |
| NESUG |
1998 |
&&&, ;;, and Other Hieroglyphics - Advanced Macro Topics |
Christopher Yindra |
|
9 |
| NESUG |
1998 |
A Smart Guide to Dummy Variables: Four Applications and a Macro |
Susan B. Garavaglia |
|
10 |
| NESUG |
1998 |
Data Mining: An Overview of Methods and Techniques for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
8 |
| NESUG |
1998 |
Information Theory Makes Logistic Regression Special |
Ernest S. Shtatland |
|
4 |
| NESUG |
1998 |
Option Pricing: A Time Series Alternative to Black-Scholes |
David R. Roberts |
|
7 |
| NESUG |
1998 |
Risk Evaluation after Heart Valve Replacement by PROC PHREG |
Choa Chen |
|
7 |
| NESUG |
1998 |
Using Logistic Regression to Predict Customer Retention |
Andrew H. Karp |
|
5 |
| SESUG |
1998 |
Applying a Robust Generalized Axis-sealing Algorithm to the Use of SAS/GRAPW |
Dorothy E. Pugb. ClinTriais |
|
2 |
| SESUG |
1998 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
7 |
| SESUG |
1998 |
Regression with Time Series Errors |
David A. Dickey |
|
9 |
| PNWSUG |
1998 |
Decision Tree Classification in Direct Marketing |
Robert Mengis |
|
9 |
| PNWSUG |
1998 |
Stepwise Anything: Reading in Regression Procedure Output for Further Testing |
Ted Clay,
Linda Remy |
|
10 |
| SEUGI |
1998 |
Data mining as a tool for Customer Selection [presentation] |
André Hønsvall,
Nils F. Haarvardsson |
source |
20 |
| SEUGI |
1998 |
Database marketing applications in the Italian banking sector |
Alberto Saccardi,
Guido Cuzzocrea |
source |
8 |
| SEUGI |
1998 |
SAS software within the Ernst & Young audit practice [presentation] |
Ton Buffing |
source |
36 |
| SUGI |
1998 |
A Revolution in Data Analysis: How New, Very Powerful, Easy to Use, Graphical Data Analysis Tools and Techniques Can Empower Even Novice Subject Matter Specialists |
Dave L. DesJardins |
source |
8 |
| SUGI |
1998 |
An Information-Gain Measure of Fit in PROC LOGISTIC |
Ernest S. Shtatland,
Mary B. Barton |
source |
6 |
| SUGI |
1998 |
Bootstrapping the Standard Error of the Mediated Effect |
Chondra M. Lockwood,
David P. MacKinnon |
source |
6 |
| SUGI |
1998 |
Graphical Presentation of a Nonparametric Regression with Bootstrapped Confidence Intervals |
Mark Nicolich,
Gail Jorgensen |
source |
5 |
| SUGI |
1998 |
Multivariable Cox Proportional Hazard Model by SAS PHREG &Validation by Bootstrapping Using SAS Randomizers With Applications Involving Electrocardiology and Organ T ransplants |
Sudhanshu K. Ghoshal |
source |
6 |
| SUGI |
1998 |
Multivariate Analysis Using the MIXED Procedure |
S. Paul Wright |
source |
5 |
| SUGI |
1998 |
Nonlinear Mixed Effects Models, a Tool for Analyzing Repeated Measurements: A Brief Tutorial Using SAS Software |
Peter P. Gaccione,
M.S. Blanchard |
source |
6 |
| SUGI |
1998 |
Robust Standard Error Estimate for Cluster Sampling Data: A SAS/IML Macro Procedure for Logistic Regression with Huberization |
Honghu Liu |
source |
6 |
| SCSUG |
1997 |
Reliability Data Analysis in the SAS System |
Gordon Johnston |
|
10 |
| PNWSUG |
1997 |
Real-World Database Marketing Experiences Using SAS Software |
Robin E. Way |
|
10 |
| WUSS |
1997 |
Analysis of Student Minimum Wage Perception Using the SAS System |
Maria Lizet Arellano,
Pedro Mercado,
John F. Killeen |
source |
4 |
| WUSS |
1997 |
Cross-Validation Estimates of the Prediction Error in a Random-Coefficients Mixed Model Used to Estimate Emissions from On-Road Motor Vehicles using SAS |
Steven Brisby |
source |
5 |
| WUSS |
1997 |
Diagnostic Plots in Regression Analysis |
George C. J. Fernandez |
source |
8 |
| WUSS |
1997 |
Factors Influencing Life Expectancy: Using SAS Regression Procedures in a Multi-Country Study |
Kamal Shoukry |
source |
5 |
| WUSS |
1997 |
Logistic Regression Modeling in Complex Surveys: Examples Using LOGITSE SAS Macro |
Jesse Albert Canchola,
Brian D. Marx,
Joseph A. Catania |
source |
10 |
| WUSS |
1997 |
Reliability Data Analysis in the SAS System |
Donna O. Fulenwider,
Gordon Johnson |
source |
10 |
| WUSS |
1997 |
SAS/SPECTRAVIEW Software and Data Mining: A Case Study |
Stuart Nisbet,
Ronald E. Stogner,
Aaron Hill |
source |
5 |
| NESUG |
1997 |
A Multivariate Analysis of Airline Service Quality |
Vasanthakumar Bhat |
|
7 |
| NESUG |
1997 |
Information as a Unifying Measure of Fit in SAS Statistical Modeling Procedures |
Ernest S. Shtatland |
|
7 |
| NESUG |
1997 |
Missing Value Imputation Methods for Large Databases |
Leonardo Auslender |
|
8 |
| NESUG |
1997 |
Nonlinear Mixed Effects Models, a tool for analyzing repeated-measurements data whose function is nonlinear in the parameters. |
Suzette Blanchard |
|
7 |
| NESUG |
1997 |
Using Logistic Regression to Test for Interaction in the Presence of Zero Cells |
Lisa Suchower |
|
10 |
| MWSUG |
1997 |
Enhancing the Output from PROC LOGISTIC |
Bharat K. Thakkar,
Kwan Hur,
Charles A. Oprian,
William G. Henderson,
Sharon Urbanski |
|
6 |
| MWSUG |
1997 |
Examining Cointegration Among Time-Series Variables Using Customized SAS Macro: Residual-Based Methods |
Jun Zuo |
|
8 |
| MWSUG |
1997 |
Linear Regression Modeling using the SAS System: A Real-World Example Comparing the Factors Influencing Charity Care and Bad Debt in Wisconsin Hospitals |
Lynette A. Gerstner |
|
7 |
| MWSUG |
1997 |
Measuring Regressor Information Content In the Presence of Collinearity |
Joseph Retzer,
Kurt Pflughoeft |
|
7 |
| MWSUG |
1997 |
Multidimensional Data Visualization Tools |
Sanjay N. Matange,
Jim Beamon,
Cynthia L. Huffman |
|
6 |
| MWSUG |
1997 |
Reliability Data Analysis in the SAS System |
Gordon Johnston |
|
10 |
| SESUG |
1997 |
Modeling Higher Education Processes with Multiple Logistic Regression: SAS Examples |
Daniel Teodorescu |
|
5 |
| SESUG |
1997 |
SAS/SPECTRAVIEW Software and Data Mining: A Case Study |
Ronald E. Stogner |
|
5 |
| SEUGI |
1997 |
Challenge your business processes with SAS software tools |
Pål Navestad |
source |
4 |
| SEUGI |
1997 |
Modelling of road deterioration including lifetime distribution and the Cox model |
Emmanuel Courilleau |
source |
11 |
| SUGI |
1997 |
&&&, ;;, and Other Hieroglyphics - Advanced Macro Topics |
Christopher Yindra |
source |
9 |
| SUGI |
1997 |
Detection of Model Specification, Outlier, and Multicollinearity in Multiple Linear Regression Models Using Partial Regression/Residual Plots |
George C. J. Fernandez |
source |
6 |
| SUGI |
1997 |
Enhancing the Output from PROC LOGISTIC |
Bharat K. Thakkar,
Kwan Hur,
Charles A. Oprian,
William G. Henderson,
Sharon Urbanski |
source |
6 |
| SUGI |
1997 |
Forecasting an Electric Utility's CO2 Emissions Using SAS/AF and SAS/STAT Software: A Linear Analysis |
Azharul Islam,
David L. Wang |
source |
5 |
| SUGI |
1997 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
source |
5 |
| SUGI |
1997 |
LOGITSE: A SAS Macro for Logistic Regression Modeling in Complex Surveys |
Jesse Albert Canchola,
Brian D. Marx,
Joseph A. Catania |
source |
6 |
| SUGI |
1997 |
Multiple Response Optimization using JMP |
Daniel J. Obermiller |
source |
7 |
| SUGI |
1997 |
SAS/SPECTRAVIEW Software and Data Mining: A Case Study |
Ronald E. Stogner,
Aaron Hill |
source |
5 |
| SUGI |
1997 |
The Parameters: A Statistical Methodology to Determine the Profit of Business Activities |
Ursula Herr,
Giovambattista Giangrieco,
Fabio Zaccaria,
Danilo Ballanti |
source |
3 |
| SCSUG |
1996 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SESUG |
1996 |
Discriminant Analysis via Statistical Packages |
Carl J Huberty,
Laureen L. Lowman |
|
11 |
| SESUG |
1996 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SESUG |
1996 |
Quasicomplete Separation in Logistic Regression: A Medical Example |
Madeline J. Boyle |
|
6 |
| NESUG |
1996 |
Forecasting Business Failures Using a Poisson Regression Model |
Vasanthakumar Bhat |
|
5 |
| NESUG |
1996 |
PC Based Direct Marketing Regression Model Production System |
Rich Masi |
|
3 |
| NESUG |
1996 |
The Bisquare Weighted Analysis of Variance: A Technique for Nonnormal Distributions |
Rebecca Regeth,
William Stine |
|
9 |
| NESUG |
1996 |
Two Many Variables, Too Little Time: A Macro Solution |
Peter Liberatore |
|
4 |
| MWSUG |
1996 |
A Set of SAS Macros for Producing Statistical Reports |
Greg A. Grandits |
|
10 |
| MWSUG |
1996 |
Testing for and Correcting for Missing Data in Survey Responses: A Survey of Downtown Business in Minneapolis |
Shelly S. Baxter,
Lawrence C. Marsh |
|
10 |
| WUSS |
1996 |
Logistic Regression: From SAS Coding to Statistical Interpretation |
Elizabeth Li |
source |
9 |
| WUSS |
1996 |
Multicollinearity in Regression Models: Detection and Remedial Measures Using the SAS System |
George C. J. Fernandez |
source |
9 |
| SEUGI |
1996 |
Motor and Household Insurance: Pricing to Maximise Profit in a Competitive Market |
Tom Wright |
source |
10 |
| SEUGI |
1996 |
Neural Networks Application: a case study |
Rui Alexandre Henriques Gonçalves |
source |
7 |
| SUGI |
1996 |
Estimating Optimal Transformations in Non-Linear Models |
Nicholas Scott Cardell,
Dan Steinberg |
source |
6 |
| SUGI |
1996 |
New Age Marketing: Past Life Regression vs. LogisticRegression |
C. Olivia Parr Rud |
source |
5 |
| SUGI |
1996 |
Using SAS Software to Perform Multivariate Adjustment of Regression Coefficients Corrected for Regression Dilution Bias |
Greg A. Grandits,
Patricia Grambsch |
source |
3 |
| SUGI |
1996 |
Using SASlETS Software to Develop a Forecasting Model |
Barbara Ledwith-Crosby |
source |
4 |
| SUGI |
1996 |
Using SLIST Catalog Entries to Store FRAME Entry Object Information |
Randy C. Finch |
source |
5 |
| MWSUG |
1995 |
An Introduction to Binary Logistic Regression |
Linda M. Quinn |
|
8 |
| MWSUG |
1995 |
Applications of PROC PHREG Enhancements in Version 6.10 |
Ying C. So |
|
9 |
| NESUG |
1995 |
Estimating MEXVAL Statistics |
Ashok Mehta |
|
5 |
| NESUG |
1995 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| WUSS |
1995 |
Applying the SAS System in Undergraduate Managerial Economics: A General Approach |
Seid M. Zekavat |
source |
5 |
| WUSS |
1995 |
Heteroskedasticity in Regression Model - Detection and Remedial Measures Using SAS 6.10 |
George C. J. Fernandez |
source |
10 |
| SESUG |
1995 |
Getting Started with PROC LOGISTIC |
Andrew H. Karp |
|
5 |
| SESUG |
1995 |
New Age Marketing: Past Life Regression versus Logistic Regression |
C. Olivia Parr Rud |
|
9 |
| SESUG |
1995 |
Using SLIST Catalog Entries to Store FRAME Entry Object Information |
Randy C. Finch |
|
5 |
| SEUGI |
1995 |
A Survival Analysis on Critical Components of Nuclear Power Plants |
Valerie Durbec |
source |
9 |
| SEUGI |
1995 |
Wouldn't it be Good if we Understood what Drives our Claims |
Kevin Williams |
source |
9 |
| SUGI |
1995 |
A Comparative Evaluation of Selected Statistical Software for Computing Various Categorical Analyses |
Nancy McDermott,
Cynthia White |
source |
6 |
| SUGI |
1995 |
An Interactive Program of the GEE Method for the Analysis of Longitudinal Data |
Masakazu Andoh,
Tohru Uwoi |
source |
6 |
| SUGI |
1995 |
Interactive Visualization and Statistical Interpretation of Market Share, Competitive Price, Stock and Mortgage Loan Data Using JMP 3.1 |
James Daughtry,
Jonathan Pinder,
Edwin Tang,
William R. Gjertsen |
source |
14 |
| SUGI |
1995 |
Karnaugh Maps, Interaction Effects and Creating Composite Dummy Variables for Regression Analysis in SAS Software |
Lawrence C. Marsh,
Karin Wells |
source |
10 |
| SUGI |
1995 |
Obtaining and Verifying Optimal Designs for Nonlinear Regression Models Using SAS Software |
Timothy E. O'Brien |
source |
6 |
| SUGI |
1995 |
Path Analysis with the CALIS Procedure: A Step-By-Step Approach to Writing the Program |
Larry Hatcher |
source |
4 |
| SUGI |
1995 |
Plotting Confidence Intervals and Prediction Bands with SAS/GRAPH Software |
Huixing Tang,
Kerril S. Bauerly,
David Swift |
source |
3 |
| WUSS |
1994 |
Empirical Analysis of Food Demand in Peru: Results and the Use of SAS Software |
Sumon Kumar Bhaumik |
source |
6 |
| WUSS |
1994 |
Factors Determining the Fluctuation of the Dow Jones Industrial Index Using SAS Procedures |
JiHong McDermott,
Anne-Marie Mowad |
source |
3 |
| WUSS |
1994 |
SAS in Taming Classical Violations |
Kamal Shoukry |
source |
3 |
| WUSS |
1994 |
Using SAS to Determine the Factors that Label College Students as "Computer Hackers" at two Los Angeles Universities |
Annaliza Dialino |
source |
3 |
| NESUG |
1994 |
PROC LOGISTIC: A Form of Regression Analysis |
Edith Flaster |
|
3 |
| NESUG |
1994 |
Using SAS/IML to Account for Spatial Dependence in Regression Models |
Charles B. Hallahan |
|
8 |
| MWSUG |
1994 |
Alternative Approaches to Mixed Linear Models |
George W. Pasdirtz |
|
6 |
| SESUG |
1994 |
Critical Steps to Meaningful Causal Data Analysis |
Deborah Wall |
|
4 |
| SEUGI |
1994 |
Practical Aspects of Modelling Techniques in Logistic Regression Procedures of the SAS System |
Josef Hogel |
source |
6 |
| SEUGI |
1994 |
The Role of SAS Software in the Analysis of the Data in a Donor Insemination Programme |
William Wallace |
source |
14 |
| SEUGI |
1994 |
Using SAS/IML Software to Develop Flexible Regression Models |
Edwin Gillespie,
Noel Wilson |
source |
5 |
| SUGI |
1994 |
Automating the Plotting of Significant Effects in Analysis of Variance |
Matthew Grover,
Huixing Tang |
source |
6 |
| SUGI |
1994 |
Avoiding, Accepting and Taking Advantage of Missing Data |
Warren Repole Jr. |
source |
9 |
| SUGI |
1994 |
Interpreting Complex Nonlinear Models |
Lawrence C. Marsh,
Maureen A. McGlynn,
Debopam Chakraborty |
source |
5 |
| SUGI |
1994 |
Neural Networks and Statistical Models |
Warren S. Sarle |
source |
13 |
| WUSS |
1993 |
A SAS Macro to Test the Significance of Differences Between Parameter Estimates in PROC CATMOD |
Linda R. Ferguson,
Mel Widawski,
Dawn M. Upchurch |
source |
5 |
| SCSUG |
1993 |
Automating the Plotting of Significant Effects in Analysis of Variance |
Huixing Tang,
Matthew Grover |
|
14 |
| SCSUG |
1993 |
Survival Analysis with SAS LIFETEST and PHREG Procedures |
Zhongmin Li |
|
10 |
| MWSUG |
1993 |
Data Ansalysis Semicolon-Free: Using SAS without the Syntax |
Julia Brooks |
|
3 |
| MWSUG |
1993 |
Designing Bank Warning System Based on Logit Model Fitted to Multi-Period Performance Data |
Sameer Kumar,
Sant R. Arora |
|
10 |
| MWSUG |
1993 |
Graphical Methods for the Interpretation of Linear Regression Models |
Simin Kavoossi,
Timothy E. Cooley |
|
7 |
| SEUGI |
1993 |
Generalised Linear Model and Correspondence Analysis. Application to the Goitre Problem in Mali |
Michel Tenehaus |
source |
28 |
| SEUGI |
1993 |
Variable Selection Techniques Implemented in Procedures of SAS Software |
Olaf Gefeller |
source |
9 |
| SUGI |
1993 |
A SAS Macro Procedure to Summarize the Output of Logistic Regression Models |
Benjamin I. Broder,
Chih-Ping Chou |
source |
6 |
| SUGI |
1993 |
A Tutorial on Logistic Regression |
Ying C. So |
source |
6 |
| SUGI |
1993 |
Likelihood Ratio Tests for Regression Coefficients from the Cox Proportional Hazards Model Using the PHREG Procedure |
Laurent M. Kassalow |
source |
6 |
| SUGI |
1993 |
MONOSEL: A SAS Macro for Model Selection in Linear Regression Analysis |
Victor Kamensky,
Ilya Muchnik |
source |
6 |
| SUGI |
1993 |
MONTE-A Risk Analysis Program |
Richard H. Fleming |
source |
6 |
| SUGI |
1993 |
Practical Econometric Analysis for Assessment of Real Property Using the SAS System on Personal Computers |
Shah Amal,
Robert Weselowski |
source |
6 |
| SUGI |
1993 |
SAS Software to Fit the Generalized Linear Model |
Gordon Johnston |
source |
8 |
| SUGI |
1993 |
The Generation of a Series of Annotated and Templated Statistical Graphs Using SAS Macros |
Susan J. Kenny |
source |
5 |
| SUGI |
1993 |
Using SAS/IML Software to Generate Odds Ratios and Associated Intervals Based on Logistic Regression Output |
Catherine O. Cowie,
Danita D. Byrd-Hol,
Keith F. Rust |
source |
6 |
| SCSUG |
1992 |
Calculating the Odds Ratio and Goodness of Fit Statistics for Logistic Regression Models Using PROC LOGISTIC |
Chuan-Chuan C. Wun |
|
19 |
| NESUG |
1992 |
An In-Depth Look at the PHREG Procedures |
Peter P. Gaccione |
|
9 |
| NESUG |
1992 |
Principles of Logistic Regression in Radiation Oncology |
J. Efird,
F. Pardo,
P. Okunieff,
D. Shoenfeld,
H. Aronen |
|
10 |
| NESUG |
1992 |
Using Macros to Create Parameter Driven Procedures that Summarize and Present Statistical Output in Tabular form |
John Wenston,
Ralph D'Agostino Jr.,
Kimbery Dukes |
|
6 |
| MWSUG |
1992 |
Marketing Research: Uncovering Competitive Advantages |
Warren F. Kuhfeld |
|
9 |
| SEUGI |
1992 |
Analysing Business and Economic Data with SAS/ETS Software |
Georg Morsing |
source |
9 |
| SEUGI |
1992 |
Cluster Characterisation wit the SAS System Factorial Analysis Solves the Problem of Synthesis Data and hte Typology of Clustering Method |
Christian Derquenne |
source |
17 |
| SEUGI |
1992 |
Marketing Research - Uncovering Competitive Advantage |
Gerhard Held |
source |
8 |
| SEUGI |
1992 |
SAS/INSIGHT Software: Introduction and New Features |
Gerhard Held |
source |
7 |
| SEUGI |
1992 |
Using SAS Macros and PROC IML to Create Special Designs for Use in Generalised Linear Models |
John Hendrickx |
source |
22 |
| SUGI |
1992 |
Analytic Modeling in SAS/INSIGHT Software |
Heman Robinson |
source |
6 |
| SUGI |
1992 |
Analyzing Business and Economics Data with SAS/ETS Software |
Mark Little |
source |
9 |
| SUGI |
1992 |
Interactive Data Analysis Strategies |
Alvin M. Best III |
source |
6 |
| SUGI |
1992 |
Marginal. Probabilities: An Intuitive Alternative to Logistic Regression Coefficients |
P. M. Wright |
source |
3 |
| SUGI |
1992 |
Marketing Research: Uncovering Competitive Advantages |
Warren F. Kuhfeld |
source |
9 |
| SUGI |
1992 |
The Investigation of Suicide Using SAS Software Procedures: A SAS/ETS Approach |
Seid M. Zekavat |
source |
6 |
| SUGI |
1992 |
The Use of Logit Analysis: Pitfalls and SAS Tips |
William Chan |
source |
3 |
| NESUG |
1991 |
Graphical Evaluation of Product Characteristics |
Melissa A. Durfee |
|
6 |
| NESUG |
1991 |
Two-Dimensional Table Look-up Procedure |
Claude Biggs |
|
6 |
| MWSUG |
1991 |
Cut the Key Entry and Contain the Corrections: Automating SAS Systems with OUTPUT and MERGE Features in Macros |
David J. Ross |
|
4 |
| SEUGI |
1991 |
Future Directions of Statistical Software with the SAS System |
David M. DeLong |
source |
20 |
| SEUGI |
1991 |
Simulation Methods Based on the SAS System |
Karin Schlauss,
Paul Muller |
source |
12 |
| SEUGI |
1991 |
Statistical Evaluation and Forecasting of Steel Corrosion Data |
Bernhard Kienzler,
Emanuel Smailos,
Rainer Koester |
source |
11 |
| SEUGI |
1991 |
Statistical Procedures in Testing the Performance of Crop Growth Simulation Models |
Ferenc Zemankovics,
Zsuzsanna Bacsi |
source |
15 |
| SUGI |
1991 |
1990 Census Mail Response and Related Variables: An Examination at the County Level Using Regression Analysis |
Jay K. Keller,
Quentin Newhouse Jr. |
source |
5 |
| SUGI |
1991 |
A Macro For Principal Component Logistic Regression |
Brian D. Marx |
source |
6 |
| SUGI |
1991 |
A Program to Compute Odds Ratios and Confidence Intervals from LOGISTIC Output |
Eric Yu I. Wang,
Aili Gong,
David P. MacKinnon |
source |
4 |
| SUGI |
1991 |
Managing Multicollinearity with the SAS System |
Rudolf J. Freund |
source |
9 |
| SUGI |
1991 |
Ridge Regression from Correlation Matrix Input |
Lawrence Hotchkiss,
John R. Gerlach |
source |
6 |
| SUGI |
1991 |
Robust Estimator for Linear Regression |
Ashok Mehta |
source |
7 |
| SUGI |
1991 |
Testing for Lack of Fit in Regression Using SAS Software |
Julie Wildman-Pepe,
Susan C. Schott |
source |
6 |
| SUGI |
1991 |
The Null Hypothesis and Regression-Based Predictions |
James A. Penny |
source |
4 |
| SUGI |
1991 |
Using SAS/IML Software to Forecast Corn and Soybean Yields |
Thomas R. Birkett |
source |
4 |
| NESUG |
1990 |
Regression Analysis In The Real World |
Edith Flaster |
|
7 |
| SEUGI |
1990 |
CITIDMSP - Citibank's Direct Marketing Software Package |
Akos Felsovalyi |
source |
12 |
| SEUGI |
1990 |
Prediciting and Understanding Steam Generator Tubes Lifetime Using SAS Software Survival Procedures |
P. Pittner,
T. Riffard |
source |
8 |
| SUGI |
1990 |
The GLIM Procedure: An Interface to the SAS System |
P. M. Grambsch,
Jon L. Kosanke,
Terry M. Therneau,
D. J. Schaid,
R. Zinsmeister,
H.S. Wieand,
Kenneth P. Offord,
J. J. LarsonKeller |
source |
5 |
| SUGI |
1990 |
Unbiased Estimators of Shrinkage for Chi-Square Based Measures of Association |
Richard F. Haase |
source |
6 |
| SEUGI |
1989 |
A Bioassay Method Using SAS/STAT Software |
C. M Fenton,
P. Blood |
source |
12 |
| SUGI |
1989 |
A Concise and Easily Interpretable Way of Presenting the Results of Regression Analyses |
Stephen Senzer,
Leland Stewart |
source |
4 |
| SUGI |
1989 |
Balanced Design Estimation |
Gordana Jelisavcic |
source |
4 |
| SUGI |
1989 |
Comparison of VMSORT, SyncSort, PLSORT and SORTT under VM/CMS Using Release 5.18 of the SAS System |
Kirsty Nunez |
source |
5 |
| SUGI |
1989 |
Handling Multicollinearity with SAS/IML Software: Ridge Regression on the PC |
Gary William Carr,
Gerald Tlapa |
source |
8 |
| SUGI |
1989 |
How to Establish a Forecasting System with SASSoftware |
Joel Fingerman |
source |
10 |
| SUGI |
1989 |
Nonlinear Measurement Error Model Parameter Estimation Using the SAS System |
Daniel Schnell |
source |
6 |
| SEUGI |
1988 |
An Iterative Weighting Procedure for Regression of Area Mortality Rate son Explanatory Variables |
Claudia Spix |
source |
6 |
| SUGI |
1988 |
Detection of Influential Observations in Logistic Regression Using the SAS System |
Charles S. Davis |
source |
6 |
| SUGI |
1988 |
Logit Models for Ordered Categorical Response Data |
Alan Agresti |
source |
9 |
| SUGI |
1988 |
New Developments in Pyschometric and Market Research Procedures |
Warren F. Kuhfeld,
Forrest W. Young |
source |
5 |
| SUGI |
1988 |
Partial Proportional Odds Models and the LOGIST Procedure |
Frank E. Harrell Jr.,
Bercedis L. Peterson |
source |
5 |
| SUGI |
1988 |
Processing and Analyzing Supermarket Scanner Data |
Charles F. Hofacker |
source |
6 |
| SUGI |
1988 |
Regression and the SAS System: An Overview |
Rudolf J. Freund |
source |
9 |
| SUGI |
1988 |
SOS: An Expert System Front-end for Analysis of Linear Models in the SAS System |
Michael P. Meredith,
Robert P. Yerex |
source |
5 |
| SUGI |
1988 |
The Use of PROC SICHAID in Marketing Research |
Jay Magidson,
Patrick Rooney |
source |
5 |
| SUGI |
1988 |
Using SAS/STAT Software's REG Procedure to Develop Sales Tax Audit Selection Models |
Kirk L. Johnson,
Richard W. Kulp |
source |
6 |
| SUGI |
1988 |
Using the SAS System to Assess Local Influence in Regression Analysis with Censored Data |
Luis A. Escobar,
William Q. Meeker Jr. |
source |
6 |
| SEUGI |
1987 |
Tutorial on PROC REG |
Gerhard Held |
source |
39 |
| SUGI |
1987 |
A Macro for Estimating the Box-Cox Power Transformation |
Andrew G. Stead |
source |
5 |
| SUGI |
1987 |
Incorporating Management Judgement in Forecasting |
Joel Fingerman |
source |
6 |
| SUGI |
1987 |
Interpretation and Diagnostics of the Multinomial Logistic Regression |
Dan Steinberg |
source |
6 |
| SUGI |
1987 |
Time Series Intervention Analysis Using SAS Software |
Terry J. Woodfield |
source |
9 |
| SUGI |
1987 |
Treatment of Lagged Dependent Regressors and Autocorrelated Errors in SAS/ETS Software |
Thomas B. Fomby,
Joseph G. Hirschberg |
source |
6 |
| SUGI |
1987 |
Using SAS Software to Develop a Prototype for Determining Participant Profiles and for Assessing Potential Relationships Among Health Insurance Variables |
Ralph F. Catalanello,
Bruce W. Eagle |
source |
6 |
| SEUGI |
1986 |
Isotonic Regression |
Arne Ran,
Bengt Johansson |
source |
10 |
| SUGI |
1986 |
A Generalized Growth Curve Procedure for the Analysis of Incomplete Longitudinal Data |
Kenneth O. Story,
Edward F. Vonesh |
source |
6 |
| SUGI |
1986 |
Analyzing Survey Data in the Electric Utility Industry Using Several SAS Procedures |
Mary Lynn Spada |
source |
4 |
| SUGI |
1986 |
Checking for Autocorrelation in Regression Residuals |
John C. Brocklebank,
David A. Dickey |
source |
7 |
| SUGI |
1986 |
Comparing Parameter Estimates Between Linear Models |
John E. Teberg |
source |
7 |
| SUGI |
1986 |
Mirror, Mirror on the Wall: A SAS Software Methodology for Plotting Corporate Image |
Luanne M. Conley |
source |
5 |
| SUGI |
1986 |
Repeated Application of a Generalized Logistic Model To Count Data Using PROC MATRIX |
Linda Williams Pickle |
source |
6 |
| SUGI |
1986 |
SAS Macros to Calculate the Full Set of Coefficients and Predicted Outcome Probabilities for a Polytomous Logit Model |
John W. Molyneaux,
Erika Mares Stone |
source |
6 |
| SUGI |
1986 |
Spline Functions for Logistic Regression Modeling |
Thomas F. Devlin,
Barbara J. Weeks |
source |
6 |
| SUGI |
1986 |
Variable Selection and Case Analysis in Regression |
Gerald R. Hobbs |
source |
6 |
| SUGI |
1986 |
Verifying Assumptions of the Cox Proportional Hazards Model |
Frank E. Harrell Jr.,
Kerry L. Lee |
source |
6 |
| SUGI |
1986 |
Weighted Ridge Estimation in a Collective Bargaining Context |
Teresa Ghilarducci,
Lawrence C. Marsh |
source |
6 |
| SEUGI |
1985 |
New Features of the SAS/ETS and SAS/OR Software in Version 5 |
John C. Brocklebank |
source |
37 |
| SEUGI |
1985 |
Test Procedures for Model Selection and Model Validation |
Wil Velding |
source |
23 |
| SUGI |
1985 |
A SAS Macro for Logistic Discrimination for Three or More Populations |
James E. Dunn,
Eileen C. King |
source |
6 |
| SUGI |
1985 |
An Application of the SAS Macro Language in a Research Environment: A Post-processor for PROC LOGIST |
Erika Mares Stone |
source |
6 |
| SUGI |
1985 |
Changes and Enhancements to SAS/ETSSoftware |
David M. DeLong,
Leigh A. Ihnen,
Mark Little |
source |
12 |
| SUGI |
1985 |
Comparison of Multivariate Regression Analysis between Logistic Model and the Least Square Model Using SAS Software |
Jane R. Bratz,
J.S. Kim,
George K. Tokuhata |
source |
4 |
| SUGI |
1985 |
Regression and Diagnostics |
Gerald R. Hobbs |
source |
8 |
| SUGI |
1985 |
The Practical Value of Logistic Regression |
Frank E. Harrell Jr.,
Kerry L. Lee |
source |
6 |
| SEUGI |
1984 |
New Statistical Features in SAS |
Gerhard Held |
source |
13 |
| SUGI |
1984 |
Analysis of Covariance-Models, Strategies and Interpretations |
George A. Milliken |
source |
10 |
| SUGI |
1984 |
BESTREG: A Procedure for Computing "BEST "Regression Subsets |
Harold W. Gugel |
source |
6 |
| SUGI |
1984 |
PROC JACKREG-A SAS Procedure for Jackknife Regression |
Daniel M. Chilko,
Panayiotis Hambi,
Gerald R. Hobbs |
source |
6 |
| SUGI |
1984 |
Proposed U.S. Passenger Car and Light Truck Sales Forecast Model |
John Janakiraman,
Stuart J. Olson Jr. |
source |
5 |
| SUGI |
1984 |
REPREG: A Repeated Measures Regression Program |
Randy L. Carter,
James T. Love |
source |
6 |
| SUGI |
1984 |
SAS Methods for the Rank Regression Model with Missing Values |
R. Michael Rubison,
Michael K. Thran |
source |
5 |
| SUGI |
1984 |
The Use of CATMOD for Repeated Measurement Analysis of Categorical Data |
Gary G. Koch,
William M. Stanish |
source |
10 |
| SEUGI |
1983 |
Graphical Methods and Regression Diagnostics |
Thore Langeland |
|
21 |
| SUGI |
1983 |
An Analysis of Time-Series Data with Autocorrelated Errors .. |
Mary S. Hirsch,
E. Moye Rutledge |
source |
3 |
| SUGI |
1983 |
Multi-Time-Period NLIN Regression |
William J. Harrison |
source |
|
| SUGI |
1983 |
Percentile Matching: An Alternative Method of Curve Fitting |
James H. Smith |
source |
5 |
| SUGI |
1983 |
PROC AID: A SAS Procedure Searching for the Best Model byStatistical Inference |
Yutaka Kimura,
Saburo Saeda,
Takashi Shitomi |
source |
5 |
| SUGI |
1983 |
PROC MCSTRAT |
Susanne L. Daood,
James M. Naessens,
Kenneth P. Offord |
source |
8 |
| SUGI |
1983 |
Robust Regression and PROC JACKREGR |
Daniel M. Chilko,
Gerald R. Hobbs |
source |
|
| SUGI |
1983 |
Urban Spatial Structure and Gasoline Consumption |
Robert M. Ray |
source |
6 |
| SUGI |
1982 |
A Comparison of Procedures for the Classification of Multivariate Observations |
Cathryn Gust,
Rebecca Klemm |
source |
4 |
| SUGI |
1982 |
Four Topics in Statistics |
Rudolf J. Freund |
source |
8 |
| SUGI |
1982 |
Influential Cases and Transformations |
R. Dennis Cook,
Sanford Weisberg |
source |
6 |
| SUGI |
1982 |
Linear Models with Dominant Variables |
Peter S. Lufkin |
source |
6 |
| SUGI |
1982 |
Variable Selection for Categorical Data Using SAS |
Erik J. Bergstralh,
Susan McGorray |
source |
6 |
| SUGI |
1982 |
Weibull Regression and Hazard Estimation |
Jan M. Hanley,
William H. Rogers |
source |
11 |
| SUGI |
1981 |
Asymmetry and Regression |
Philip Harris Monchar |
source |
5 |
| SUGI |
1981 |
Estimation of Fixed Effects in Mixed Models with Unbalanced Data |
Walter R. Harvey |
source |
7 |
| SUGI |
1981 |
How to Use SAS for ANOVA of Mixture Problems |
Mark L. Tiede |
source |
7 |
| SUGI |
1981 |
Influential Data Diagnostics and Model Building Techniques Applied to an Air Pollution and Mortality Analysis |
Diane I. Gibbons,
Gary C. McDonald |
source |
|
| SUGI |
1981 |
Plotting Confidence Bands Using PROC GLM and PROC REG |
Curtis Barton |
source |
6 |
| SUGI |
1980 |
A Measure of Predictive Performance for Estimation When the Predicted Value is a Probability |
Josefina A. Lago |
source |
6 |
| SUGI |
1980 |
An Overview of Survival Analysis and SAS |
Irving K. Hwang |
source |
|
| SUGI |
1980 |
n Annotated Guide to the Analysis of Linear Models Using SAS |
Rudolf J. Freund,
Ramon C. Littell |
source |
6 |
| SUGI |
1980 |
Regression with Linear Splines and Plateaus |
Samuel G. Carmer,
Wen T. Hsieh,
William M. Walker |
source |
|
| SUGI |
1980 |
Threshold Point Models: A SAS Macro for Estimation of Parameters |
George A. Milliken,
Jeanne L. Sebaugh |
source |
6 |
| SUGI |
1979 |
A SAS Macro for Ridge Analysis of Multivariate General Linear. Models |
Kenneth A. Hardy,
Again N. Sinha |
source |
5 |
| SUGI |
1979 |
An Evaluation of Nonlinear Regression Programs |
C. M. Metzler |
source |
9 |
| SUGI |
1979 |
DESIGN, a Macro for Constructing Optimum Experimental Designs |
Ed R. Jones |
source |
6 |
| SUGI |
1979 |
Estimating the Parameters of Biological Models Using SAS |
Thomas P. Capizzi,
Karen Kral,
Robert D. Small |
source |
7 |
| SUGI |
1979 |
Exploring Biased Regression with'SAS |
Samuel G. Carmer,
Wen T. Hsieh |
source |
6 |
| SUGI |
1979 |
Procedures for Analysis of Survival Data |
Terry M. Therneau |
source |
5 |
| SUGI |
1978 |
A SAS Macro for Calculating Coefficients of Ridge Regression |
Ernest Hilderbrand,
Robert Rogers |
source |
7 |
| SUGI |
1978 |
Multivariate Prediction of Neonatal Mortality with Emphasis on Health Care Inputs |
Merwyn R. Greenlick,
Jonathan D. Quick |
source |
6 |
| SUGI |
1978 |
Response Surface Contour Plotting in SAS |
Daniel M. Chilko |
source |
4 |
| SUGI |
1978 |
Some Applications of the Discriminant Function Procedure |
Emilio A. Icaza,
Kenneth L. Koonce |
source |
4 |
| SUGI |
1978 |
Use of MATRIX for Single Degree of Freedom Contrasts in Factorial Experiments. |
Samuel G. Carmer |
source |
4 |
| SUGI.ONE |
1976 |
Econometric Uses of SAS |
Max Moszer,
Martha S. Shuler |
source |
26 |
| SUGI.ONE |
1976 |
Two Tools for Residual Analysis in Multiple Regression |
Ronald B. Wiley |
source |
36 |
| SUGI.ONE |
1976 |
Using SAS for Univariate Time Series Analysis via the Box Jenkins Technique |
Mark J. Nicolich |
source |
20 |
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