5.2. Cox Regression
The most popular method for analyzing event history data is Cox regression, named after its inventor, David Cox (1972), who introduced the proportional hazards model and the partial likelihood method for estimating that model. Before we discuss fixed effects analysis, it's essential to review this method.
Rather than directly modeling the length of the interval, the dependent variable in Cox regression is the hazard, or instantaneous likelihood of event occurrence. For repeated events, the hazard may be defined as follows. Let Ni(t) be the number of events that have occurred to individual i by time t. The hazard for individual i at time t is given by
In words, this equation says to consider the probability of one additional ...
Get Fixed Effects Regression Methods for Longitudinal Data Using SAS now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
