@article{ref1,
title="Discrete-Time Survival Factor Mixture Analysis for Low-Frequency Recurrent Event Histories",
journal="Research in human development",
year="2009",
author="Masyn, Katherine E.",
volume="6",
number="2/3",
pages="165-194",
abstract="In this article, the latent class analysis framework for modeling single event discrete-time survival data is extended to low-frequency recurrent event histories. A partial gap time model, parameterized as a restricted factor mixture model, is presented and illustrated using juvenile offending data. This model accommodates event-specific baseline hazard probabilities and covariate effects; event recurrences within a single time period; and accounts for within- and between-subject correlations of event times. This approach expands the family of latent variable survival models in a way that allows researchers to explicitly address questions about unobserved heterogeneity in the timing of events across the lifespan.<p />",
language="",
issn="1542-7609",
doi="10.1080/15427600902911270",
url="http://dx.doi.org/10.1080/15427600902911270"
}