Survival analysis in Python

Survival analysis is used to model durations, such as the time to an event, or other values that for some reason may be right censored (i.e. we don’t observe the event time for every subject).  They are widely used in medical and social research, and in engineering.  The Python Statsmodels package allows most of the common forms of survival analysis to be carried out in Python.  In this workshop we will briefly review basic survival analysis methodology, and illustrate its use through case studies.  The primary emphasis will be marginal survival distribution estimation (the Kaplan-Meier method) and proportional hazards regression (the Cox model).

rescheduled from May 4, 2017