Survival Analysis in SAS

The basic theory of survival analysis will be reviewed, with implementation in SAS procedures including descriptive analyses and multivariable modeling using both parametric and non-parametric methods. Common pitfalls will be discussed, along with some extensions including use of time-dependent covariates and recurrent event analyses.

About the Presenter

Abigail Smith, PhD, MS, is a biostatistician with research interests in survival and recurrent event analysis and machine learning. She received her PhD from the University of Michigan in 2016. Dr. Smith is currently the Scientific Director for the Scientific and Data Coordinating Centers Program at Arbor Research Collaborative for Health. She currently provides statistical leadership to several Data Coordinating Centers including the Symptoms of Lower Urinary Tract Dysfunction Research Network (LURN), where she serves as Deputy Program Director, and the Cure Glomerulonephropathy Network (CureGN), and the Nephrotic Syndrome Study Network (NEPTUNE) where she serves as a co-investigator. She is also part of the program team administering the National Living Donor Assistance Center (NLDAC), which provides financial support to living donors. She has expertise in a variety of statistical methods including regression, longitudinal and survival analysis, missing data methods, and supervised and unsupervised machine learning methods as well as clinical research in urology, chronic kidney disease, and transplantation.