| PharmaSUG |
2022 |
Simple and Efficient Bootstrap Validation of Predictive Models Using SAS/STAT Software |
Matthew T. Slaughter, Isaiah Lankham |
source |
22 |
| SGF |
2021 |
A Framework for Simple and Efficient Bootstrap Validation in SAS, with Examples |
Isaiah Lankham, Matthew T. Slaughter |
source |
22 |
| SGF |
2019 |
SCORE! Techniques for Scoring Predictive Regression Models Using SAS/STAT Software |
Phil Gibbs, Randy Tobias |
source |
18 |
| MWSUG |
2018 |
Tips, Tricks, and Traps on Longitudinal Data Analysis with Discrete and Continuous Times |
Brandy R. Sinco, Edith Kieffer, Michael S. Spencer, Gray Ficker, Gretchen Piatt |
|
20 |
| MWSUG |
2016 |
Use Multi-Stage Model to Target the Most Valuable Customers |
Chao Xu, Jing Ren, Hongying Yang |
|
10 |
| MWSUG |
2016 |
Using SAS to Generate p-Values with Monte Carlo Simulation |
Brandy R. Sinco, Edith Kieffer, Michael S. Spencer, Michael Woodford, Gloria Palmisano, Gretchen Piatt, Michele Heisler |
|
14 |
| MWSUG |
2015 |
Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software |
Jill Tao, Kathleen Kiernan, Phil Gibbs |
|
18 |
| WUSS |
2015 |
Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software |
Phil Gibbs, Jill Tao, Kathleen Kiernan |
source |
18 |
| PharmaSUG |
2015 |
Confidence Intervals Are a Programmer's Friend |
Xinxin Guo, Zhaohui Su |
source |
8 |
| SGF |
2015 |
Advanced Techniques for Fitting Mixed Models Using SAS/STAT Software |
Kathleen Kiernan |
source |
18 |
| SGF |
2015 |
Using and Understanding the LSMEANS and LSMESTIMATE Statements |
David J. Pasta |
source |
20 |
| SESUG |
2014 |
Making Comparisons Fair: How LS-Means Unify the Analysis of Linear Models |
Weijie Cai |
source |
22 |
| WUSS |
2014 |
Using and Understanding LSMEANS and LSMESTIMATE |
David J. Pasta |
source |
20 |
| SGF |
2014 |
Making Comparisons Fair: How LS-Means Unify the Analysis of Linear Models |
Weijie Cai |
source |
22 |
| SGF |
2013 |
Being Continuously Discrete (or Discretely Continuous): Understanding Models with Continuous and Discrete Predictors and Testing Associated Hypotheses |
David J. Pasta |
source |
19 |
| WUSS |
2012 |
Being Continuously Discrete (or Discretely Continuous): Understanding Models with Continuous and Discrete Predictors and Testing Associated Hypotheses |
David J. Pasta |
source |
19 |
| PharmaSUG |
2011 |
CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement |
Kathleen Kiernan, Randy Tobias, Phil Gibbs, Jill Tao |
source |
19 |
| SGF |
2011 |
CONTRAST and ESTIMATE Statements Made Easy: The LSMESTIMATE Statement |
Kathleen Kiernan, Randy Tobias, Phil Gibbs, Jill Tao |
source |
19 |
| SGF |
2011 |
Visualizing Marginal Effects from Interactions in Generalized Linear Models |
Xiao Chen, Brigid Wilson |
source |
7 |
| SGF |
2010 |
Everything in Its Place: Efficient Geostatistical Analysis with SAS/STAT Spatial Procedures |
Alexander Kolovos |
source |
18 |
| SGF |
2010 |
Introducing PROC PLM and Postfitting Analyses in Very General Linear Models |
Randy Tobias, Weijie Cai |
source |
18 |