Survival Analysis Using SAS®: A Practical Guide

Why Use Survival Analysis?

Survival data have two common features that are difficult to handle with conventional statistical methods: censoring and time-dependent covariates (sometimes called time-varying explanatory variables). Consider the following example, which illustrates both these problems. A sample of 432 inmates released from Maryland state prisons was followed for one year after release (Rossi et al. 1980). The event of interest was the first arrest. The aim was to determine how the occurrence and timing of arrests depended on several covariates (predictor variables). Some of these covariates (like race, age at release, and number of previous convictions) remained constant over the one-year interval. Others (like marital status and ...