The Logit Model for Discrete Time

We begin with the logit version of the model because it is more widely used and because logit regression is already familiar to many readers. In Chapter 5 (see The DISCRETE Method), we considered Cox’s model for discrete-time data. In brief, we let Pit be the conditional probability that individual i has an event at time t, given that an event has not already occurred to that individual. The model says that Pit is related to the covariates by a logistic regression equation:

Equation 7.1

where t = 1, 2, 3,.... This model is most appropriate when events can only occur at regular, discrete points in time, but ...

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