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multiple regression

111 papers and 2 presentations; 106 titles.

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Conference × Year × Title × Authors Extras Pages
WUSS 2026 Demystifying Regression Analysis Techniques with R Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao		 35
PharmaSUG 2026 Regression Analysis Made Easy Using R Zheyuan Yu,
Kirk Paul Lafler,
Zichun Gao,
Jiaxin Xu,
Zeqi Li,
Ruochen Shao		 source 32
PHUSE US 2026 Robust Causal Inference in Real-World Evidence Studies with Double Machine Learning Yilun Huang,
Jing Dai		 source
presentation source		 5
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
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
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
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
SGF 2020 %SURVEYCORRCOV Macro: Complex Survey Data Correlations for Multivariate Analysis and Model Building David R. Nelson,
Siew Wong-Jacobson		 source 20
SESUG 2019 Advanced Statistical Modeling within Machine Learning and Big Data Analytics Niloofar Ramezani,
George Mason		 source 16
SGF 2019 Conducting Tests in Multivariate Regression Chii-Dean Joey Lin source 13
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
WUSS 2018 Oops, I D-I-D It Again! Advanced Difference-in-Differences Models in SAS Margaret Warton,
Melissa Parker		 source 17
PharmaSUG 2018 Multicollinearity: What Is It and What Can We Do About It? Deanna Naomi Schreiber-Gregory source 13
SGF 2018 Multiple Regression Diagnostics in SAS: Predicting House Sale Prices [presentation] Karen Bui source 7
SGF 2018 Prediction and Interpretation for Machine Learning Regression Methods David Richard Cutler source 16
SESUG 2017 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation Methods on Point and Interval Estimates when Data are MCAR, MAR, and MNAR Listwise Deletion source 26
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
WUSS 2017 Multicollinearity: What Is It and What Can We Do About It? Deanna Naomi Schreiber-Gregory source 12
SGF 2017 Multicollinearity: What Is It, Why Should We Care, and How Can It Be Controlled? Deanna Naomi Schreiber-Gregory source 12
SGF 2017 What Statisticians Should Know about Machine Learning David Richard Cutler source 13
SCSUG 2016 Optimization of Refining Crude Distillation Process Unit using Process Simulation and Statistical Modeling Methods Jose Bird source 18
SESUG 2016 Missing Data and Complex Sample Surveys Using SAS: The Impact of Listwise Deletion vs. Multiple Imputation on Point and Interval Estimates when Data are MCAR and MAR Anh P. Kellermann,
DeAnn Trevathan,
Jeffrey D. Kromrey		 source 12
SESUG 2016 Using JMP to apply Decision Trees and Random Forests as Screening Tools for Limiting Candidate Predictors in Regression Models Jason Brinkley source 10
SESUG 2016 Using SAS to Examine Relationships among Leadership Styles of College of Nursing Deans and Faculty Job Satisfaction Levels in Research Intensive Institutions Nursing Deans,
Faculty Job Satisfaction Levels		 source 6
MWSUG 2016 A Demonstration of Various Models Used in a Key Driver Analysis Steven M. LaLonde 17
SGF 2016 Transforming Data to Information in Education: Stop with the Point-and-Click!!! Sean W. Mulvenon source 9
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
SCSUG 2015 Optimization of Refining Alkylation Process Unit using Response Surface Methods Jose Bird,
Darryl Seillier		 source 20
WUSS 2015 Data Analyses in Multivariate Regression Chii-Dean Joey Lin source 9
WUSS 2015 SAS at Los Angeles County Assessor's Office Anthony Liu source 20
SGF 2015 Sums of Squares: The Basics and a Surprise Sheila Barron,
Michelle Mengeling		 source 8
MWSUG 2014 Measuring Product-level Promotional Effectiveness using Multiple Linear Regression Aaron Clark,
Cory Weinmann,
Donald Kirk		 10
MWSUG 2014 Understanding Change through Different Methodological Lens Jie Liao 12
SGF 2014 Intermittent Demand Forecasting and Multi-tiered Causal Analysis Edward Katz source 11
SESUG 2013 SAS Macros to Conduct Common Biostatistical Analyses and Generate Reports Dana Nickleach,
Yuan Liu,
Adam Shrewsberry,
Kenneth Ogan,
Sungjin Kim		 source 8
SGF 2013 Regression of NASCAR: Looking into Five Years of Jimmie Johnson Alex Herrington,
Liuchun Yang,
Yun Gao		 source 20
PHUSE EU 2012 Multicollinearity Diagnostics in Statistical Modeling and Remedies to Deal with it Using SAS Harshada Joshi,
Swapna Deshpande		 source
presentation source		 12
SESUG 2012 Spatial Analysis of Gastric Cancer in Costa Rica using SAS Software So Young Park,
Marcela Alfaro-Cordoba		 source 8
MWSUG 2012 Testing the Bayesian Suite of SAS Procedures using Ecological Data and Comparing Simulations with WinBUGS Matthew Russell 8
WUSS 2012 How Do Child Support Order Amounts Affect Payments and Compliance? Mark Takayesu source 12
WUSS 2012 The Steps to Follow in a Multiple Regression Analysis Theresa H. Ngo source 12
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 The Steps to Follow in a Multiple Regression Analysis Theresa H. Ngo source 12
SCSUG 2011 An Introductory Look at the Situational Context Inherent in the RBI Using Two Modeling Approaches Ryan Sides source 14
SESUG 2011 An Exact Implicit Enumeration Algorithm for Variable Selection in Multiple Linear Regression Models Using Information Criteria Dennis J. Beal source 12
WUSS 2011 Statistical Analyses Using SAS Enterprise Guide R. Scott Leslie source 11
WUSS 2010 An Introduction to Statistical Tests for the SAS Programmer Sara Beck source 10
MWSUG 2010 Adequacy and Information Values: Two Tools for Ranking Predictors in Generalized Linear Models Douglas Thompson 21
PharmaSUG 2010 Using SAS to Compute Partial Correlation Jianxin Lin,
Aiming Yang,
Arvind Shah		 5
PNWSUG 2009 Building Multiple Linear Regression Models - Food for Thought Colleen E. McGahan,
Mei Chong		 11
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
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
MWSUG 2008 Experimental Learning: Use of JMP Journal in Six Sigma Green and Black Belt Training Amurthur Ramamurthy,
Paul Cook		 16
SGF 2008 Integrating Consumer Demand to Improve Shipment Forecasts Charles Chase source 10
NESUG 2007 Using PROC GENMOD to Model Adverse Event Counts in a Healthcare Setting John Ulicny,
Thomas Klumpp		 13
SESUG 2007 Information Criteria Methods in SAS for Multiple Linear Regression Models Dennis J. Beal source 10
WUSS 2007 Using the NPAR1WAY Procedure to Investigate Philanthropy Preference Survey Data Joseph E. Earley,
Kimberly Rodriguez		 source 7
SGF 2007 OLS Regression? Auto-Regression? Dynamic Regression? Rodger Zhang source 12
WUSS 2006 Environmental Samples Below the Limits of Detection - Comparing Regression Methods to Predict Environmental Concentrations Daniel Smith,
Elana Silver,
Martha Harnly		 source 8
NESUG 2006 Using PROC GENMOD to Model Adverse Event Counts in a Healthcare Setting John Ulicny,
Thomas Klumpp		 13
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
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
SUGI 2005 Structured Neural Network Techniques for Modeling Loyalty and Profitability Carl Lee,
Tim Rey,
James W. Mentele,
Michael Garver		 source 13
WUSS 2004 Evaluating Student Statistics Performance Using SAS/STAT Procedures Seid M. Zekavat,
Kathryn Wilson		 source 5
WUSS 2003 Adaptive Regression in SAS/IML David Katz source 5
WUSS 2003 Regression Diagnostic Plots George C. J. Fernandez source 9
WUSS 2003 Using SAS IN Educational Research Leping Liu source 6
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 Multiple Linear Regression Analysis of Total Mercury Levels in Blood and Urine Samples Miki Yamauchi,
George C. J. Fernandez,
Stanley Omaye		 source 6
NESUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe 13
WUSS 2001 Using SAS to Assess Students' Learning in Instructional Technology Courses Leping Liu source 6
SESUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe source 13
SCSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 13
PharmaSUG 2001 Power and Sample Size Determination for Linear Models John M. Castelloe 14
SUGI 2001 Power and Sample Size Determination for Linear Models John M. Castelloe,
Ralph G. O'Brien		 source 13
WUSS 2000 SAS STAT applications in Econometrics Mathura Thillainathan,
George C. J. Fernandez		 source 10
MWSUG 2000 The Development of the Ohio State Highway Patrol's Cadet Allocation Model Gary M. Macklis 3
SEUGI 2000 Two sides to the modelling problem [presentation] Philip Whittall source 14
PharmaSUG 2000 Visualize Your Regression Analysis Fan Xu 7
WUSS 1999 Combining SAS Data Sets in Educational Research Leping Liu,
George C. J. Fernandez		 source 6
WUSS 1999 Evaluating Student Performance in Statistics Using SAS/ETS Procedures Seid M. Zekavat,
Marianna Fratkina		 source 4
MWSUG 1999 Longitudinal Data Analysis Repeated-Measure ANOVA and Mixed Models Nancy E. Briggs,
Ching-Fan Sheu		 6
SUGI 1999 Stepwise Regressor Selection for Interdependence Analysis and Multivariate Multiple Regression James E. Dunn,
Lynette K. Duncan		 source 6
SUGI 1999 Using SAS to Conduct Pilot Studies: An Instructors Guide Sean W. Mulvenon,
Ronna C. Turner		 source 6
WUSS 1998 Multiple Regression and Model Selection on Developing a Computer Achievement Model Leping Liu,
George C. J. Fernandez		 source 6
SUGI 1998 Improving the Rainbow Test: A Macro to Measure the Lack of Fit in Multiple Regression with the Use of the Bootstrap Paul W. Johnson source 4
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
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
WUSS 1996 Multicollinearity in Regression Models: Detection and Remedial Measures Using the SAS System George C. J. Fernandez source 9
SUGI 1996 Using SASlETS Software to Develop a Forecasting Model Barbara Ledwith-Crosby source 4
SEUGI 1994 ATMOSFERA a Computer System Developed with SAS Software for Management, Forcasting and Analysis of Metereological Data and Atmospheric Pollution in Urban Territory Data P. Fedelel,
G. Grandoni,
M. C. Mammarella,
G. Marcon,
M. Sanarico		 source 11
SEUGI 1993 Generalised Linear Model and Correspondence Analysis. Application to the Goitre Problem in Mali Michel Tenehaus source 28
SCSUG 1992 A Scoring System for Sales Tax Audit Selection Thomas J. Winn Jr. 10
SEUGI 1990 The Accuracy of Statistical Software F. Pierri,
G. Galmacci		 source 9
SEUGI 1990 The Use of Input-Output Analysis for the Evaluation of Macroeconomic Impact of Electricity Tariffs Policy A Menu Driven System F. Mattei,
Penteriani,
T. Ledda		 source 10
NESUG 1989 Supporting Academic Statistics: SAS and the Individual Researcher Richard White 2
SUGI 1989 Weighted Multicollinearity Diagnostics for Logistic Regression Brian D. Marx,
Eric P. Smith		 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
SUGI 1986 Comparing Parameter Estimates Between Linear Models John E. Teberg source 7
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 The Practical Value of Logistic Regression Frank E. Harrell Jr.,
Kerry L. Lee		 source 6
SUGI 1985 The SAS Biostatistical Workbook: Bridging the Gaps Between Statistical Methods, Statistical Applications, and Statistical Computing David A. Ludwig source 6
SUGI 1983 Robust Regression and PROC JACKREGR Daniel M. Chilko,
Gerald R. Hobbs		 source
SUGI 1982 Iowa Survey of Dental Health: Stepwise Regression Results J.D. Beck,
J. Jakobsen,
B. Townsend		 source 5
SUGI 1982 The Analysis of Ecological Survey Data with SAS and EAP Robert W. Smith source
SUGI 1981 Diagnostic Techniques in Multiple Linear Regression Using PROC MATRIX Ronald R. Hocking,
O. J. Pendleton		 source 7
SUGI 1980 Slope Ratio Bioassay Using SAS Janet E. Field,
Rudolph S. Parrish,
Glenn O. Ware		 source
SUGI 1979 A SAS Macro for Robust Multiple Regression Charles McElrea source 4
SUGI 1978 Multivariate Prediction of Neonatal Mortality with Emphasis on Health Care Inputs Merwyn R. Greenlick,
Jonathan D. Quick		 source 6
SUGI.ONE 1976 A Comparison of BMD, SAS and SPSS T. Papaioannou,
G.P.H. Styan,
L.L. Ward		 source 21
SUGI.ONE 1976 Two Tools for Residual Analysis in Multiple Regression Ronald B. Wiley source 36

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