PharmaSUG2016paper·US·Quick Tips
PROC SQL: To Create Macro Variables with Multiple Values and the Uses in Clinical Programming QT18
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PharmaSUG2016paper·US·Quick Tips
SAS® Abbreviations: a Shortcut for Remembering Complicated Syntax QT20
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Cox proportional hazards regression to model the risk of outcomes per double increase in a continuous explanatory variable SP01
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Programming Support for Exposure-Response Analysis in Oncology Drug Development SP03
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Scrambled Data – A Population PK/PD Programming Solution SP04
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Unequalslopes: Making life easier when the proportional odds assumption fails SP05
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
A Dose Escalation Method for Dual-Agent in Phase 1 Cancer Clinical Trial using the SAS MCMC Procedure SP06
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Latent Structure Analysis Procedures in SAS® SP07
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Everything or Nothing – A Better Confidence Intervals for Binomial Proportion in Clinical Trial Data Analysis SP08
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
Simulation of Data using the SAS System, Tools for Learning and Experimentation SP09
PharmaSUG2016paper·US·Statistics and Pharmacokinetics
ROC Curve: Making way for correct diagnosis SP11
PharmaSUG2016paper·US·Submission Standards
Creating Define-XML version 2 including Analysis Results Metadata with the SAS® Clinical Standards Toolkit SS01
PharmaSUG2016paper·US·Submission Standards
Preparing Legacy Format Data for Submission to the FDA – When & Why Must I Do It, What Guidance Should I Follow? SS02