| PHUSE US |
2026 |
A Proc Compare Enhancement Macro |
Chris Weiner |
source presentation source |
12 |
| PHUSE US |
2023 |
Tidytlg: An R Package for Clinical Reporting Using Tidyverse |
Sheng-Wei Wang |
source presentation source |
9 |
| PHUSE EU |
2020 |
MI FOR MI, OR HOW TO HANDLE MISSING INFORMATION WITH MULTIPLE IMPUTATION |
Daria Shamaida |
source video presentation source |
8 |
| SGF |
2020 |
Automation in SAS Visual Data Mining and Machine Learning |
Wendy Czika |
source |
26 |
| SESUG |
2019 |
Medians/quartiles are shown for continuous data and counts/percentages are shown for categorical data |
Martha Wetzel |
source |
5 |
| SGF |
2019 |
Using SAS Macros to Analyze Lifetime Data with Left Truncation |
Zhen-Huan Hu |
source |
11 |
| PHUSE US |
2019 |
Integrative Analysis of Circulating Tumor Cell Counts and Gene Expression Levels |
Yauheniya Cherkas |
source presentation source |
8 |
| SCSUG |
2018 |
Machine Learning in Litigation Prediction - Workers' Compensation Litigation Propensity Predictive Model |
Mei Najim |
source |
17 |
| WUSS |
2018 |
An Efficient Way to Output Univariate Analysis Results with Multiple Predictors |
Bocheng Jing, Kathy Fung, W. John Boscardin |
source |
7 |
| PharmaSUG |
2018 |
Second Primary Malignancy (SPM) Analyses in a Disease Registry Study |
Jane Lu, Shankar Srinivasan, Robert Knight |
source |
6 |
| SGF |
2018 |
Claim Analytics: A Litigation Prediction Case Study |
Mei Najim |
source |
18 |
| SGF |
2018 |
Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures |
Gerhard Svolba |
source |
26 |
| MWSUG |
2017 |
Claim Analytics |
Mei Najim |
|
18 |
| SGF |
2017 |
Property and Casualty Insurance Predictive Analytics in SAS |
Mei Najim |
source |
17 |
| 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 |
| MWSUG |
2016 |
Property and Casualty Insurance Predictive Analytics in SAS |
Mei Najim |
|
17 |
| SGF |
2016 |
A Property and Casualty Insurance Predictive Modeling Process in SAS |
Mei Najim |
source |
14 |
| MWSUG |
2015 |
A Property & Casualty Insurance Predictive Modeling Process in SAS |
Mei Najim |
|
14 |
| SESUG |
2014 |
To foam or not to foam: A survival analysis of the foam head that forms when a soda is poured |
Kate Phillips |
source |
16 |
| PharmaSUG |
2014 |
Survival Analysis Approaches and New Developments using SAS |
Jane Lu, David Shen |
source |
13 |
| WUSS |
2013 |
Telling Stories with Your Data - Graphs, Tables and Basic, Basic Statistics with SAS Enterprise Guide |
AnnMaria De Mars |
source |
19 |
| WUSS |
2013 |
Weighting Multiple Years to Identify Trends: A Logistic Regression of Public Use Data |
Marie Boman-Davis |
source |
5 |
| SGF |
2012 |
An Automatic Approach to Creating a Data Dictionary in SharePoint Using SAS |
Kevin Chung |
source |
17 |
| WUSS |
2011 |
SAS Essentials III: Statistics for Hamsters |
AnnMaria De Mars |
source |
18 |
| SGF |
2011 |
Highlighting Unusual Behavior in Insurance Based on Social Network Analysis |
Carlos Andre R. Pinheiro |
source |
9 |
| MWSUG |
2010 |
Tips for Automating Univariate Outcomes Analysis in Hematopoietic Stem Cell Transplantation |
Peigang Li, Xiaochun Zhu, Min Chen |
|
7 |
| NESUG |
2008 |
Box Plots in SAS: UNIVARIATE, BOXPLOT, or GPLOT? |
Robert Adams |
|
11 |
| PharmaSUG |
2008 |
Automated SAS Macro for Adverse Event Logistic Regression Analysis |
Suhas R. Sanjee |
|
8 |
| SESUG |
2006 |
Creating RTF Tables with Univariate Analyses of Multiply Imputed Data |
Marie Gantz |
source |
14 |
| PharmaSUG |
2005 |
Program Templates for Report Generation |
Roger J. DeAngelis, Thousand Oaks |
|
9 |
| SEUGI |
2003 |
Predicting churn behaviour for Optimus [presentation] |
Ricardo Almedia |
source |
20 |
| MWSUG |
2001 |
Modeling Lifetime Value in the Insurance Industry |
C. Olivia Parr Rud |
|
9 |
| SUGI |
2001 |
Modeling Lifetime Value in the Insurance Industry |
C. Olivia Parr Rud |
source |
8 |
| SESUG |
2000 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
7 |
| NESUG |
2000 |
NPV Modeling for Direct Mail Insurance |
C. Olivia Parr Rud |
|
7 |
| WUSS |
2000 |
Using PROC FACTOR to Conduct an Exploratory Factor Analysis of Self Reported Symptom Data |
Tyler C. Smith |
source |
6 |
| SEUGI |
2000 |
A Web Presentation of a SAS data set from the Uppsala Longitudinal Study of Adult Men (ULSAM) |
Hans Lithell, Lars Bergulund, Liisa Byberg, Rawya Mohsen |
source |
10 |
| SEUGI |
2000 |
The Art of Building Predictive Scorecards [presentation] |
Duncan Hale |
source |
15 |
| SESUG |
1999 |
Analysis of Longitudinal Data: Comparison between PROC GLM and PROC MIXED |
Maribeth H. Johnson |
source |
6 |
| SESUG |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
7 |
| WUSS |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
source |
6 |
| NESUG |
1999 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
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 |
| WUSS |
1998 |
The Capabilities of PROC FACTOR to Conduct an Exploratory Factor Analysis |
Tyler C. Smith |
source |
6 |
| NESUG |
1998 |
Data Mining: An Overview of Methods and Techniques for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
8 |
| SESUG |
1998 |
Data Mining: An Overview of Methods and Technologies for Increasing Profits in Direct Marketing |
C. Olivia Parr Rud |
|
7 |
| SEUGI |
1998 |
GLM and MIXED procedures to treat longitudinal data |
Sandrine Laguerre |
source |
9 |
| SEUGI |
1998 |
The actuary laboratory [presentation] |
Paolo Loi, Stephano Ferri |
source |
7 |
| SUGI |
1994 |
Introduction to Repeated Measures |
William G. LeBlanc |
source |
9 |
| SUGI |
1993 |
SAS Data Dictionary Tool Box |
Allan E. Williams, Peter Dueber, Lynette M. Browne |
source |
5 |
| SUGI |
1990 |
The SAS System as Simulation Language: An Application to Tunnel Construction Modeling |
Ronald R. MacDonald, Shi-Tao Yeh, Guillermo F. Salazar |
source |
6 |
| SUGI |
1988 |
Repeated Measures Analysis with the SAS System |
Ramon C. Littell, Jane Pendergast |
source |
7 |
| SEUGI |
1985 |
A Help for End-Users SAS Software for Analysis of Surveys |
Gerard Hatabian |
source |
10 |
| SEUGI |
1984 |
New Statistical Features in SAS |
Gerhard Held |
source |
13 |
| SUGI |
1983 |
Univariate and Multivariate Repeated Measures Analysis Through PROCs REG, GLM, and MATRIX |
Robert S. Barcikowski, Randall R. Robey |
source |
6 |
| SUGI |
1982 |
SAS Procedures for ANOVA or Repeated Measures Designs |
William G. Jackson Jr., Richard C. McNee, Carolyn J. Oakley |
source |
2 |
| SUGI |
1980 |
Analysis of Repeated Measures Experiments: One- and Two-way Classifications |
Louis Bonus, Harji I. Patel |
source |
6 |