TITLE

Latent class models and their application to missing-data patterns in longitudinal studies

AUTHOR(S)
Roy, Jason
PUB. DATE
October 2007
SOURCE
Statistical Methods in Medical Research;Oct2007, Vol. 16 Issue 5, p441
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Latent class models have been developed as a flexible way of modeling the correlation of multivariate data, as a method for discovering subpopulations with similar response profiles and as a dimension reduction tool. In this manuscript, we provide a review of some of this literature and describe specific developments in several statistical and substantive areas. We then describe latent class models that could be used for characterizing missing-data patterns in longitudinal studies with regularly spaced observation times,where there is a large amount of intermittent missing data. We illustrate by analyzing data from a longitudinal study of depression, where there were 379 unique missing-data patterns.
ACCESSION #
26663023

 

Related Articles

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics