Event history analysis (also known as survival analysis) is a branch of statistics that focuses on the analysis of time duration until one or more events occur, such as time to first marriage. It is a critical method for those who wish to ask questions about predictors of the time to certain discrete events when censoring is a concern (i.e., when the event of interest does not occur before data collection ends). 

This seminar will be of interest to researchers in many disciplines such as criminology, clinical psychology, epidemiology, education, medicine, and economics. Some examples of research questions that can be answered with this method include:

• Is BMI a significant predictor of time to smoking cessation?
• Does financial aid influence time to recidivism of released inmates?
• Does time to recovery from Anxiety Disorder differ between competing types of psychotherapy?
• Does early language ability influence time to reclassification for limited English-proficient students? 

This methodology talk will provide a brief introduction to event history analysis, as well as numerous worked examples and instruction in how to execute them in the R statistical software package.  Participants will also be provided with sample code (available in R and STATA) and other resources to apply to their own work.