Citation

Masyn KE. Res. Hum. Dev. 2009; 6(2/3): 165-194.

Copyright

(Copyright © 2009, Informa - Taylor and Francis Group)

DOI

10.1080/15427600902911270

PMID

unavailable

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.