Latent mixture models for multivariate and longitudinal outcomes.

Abstract:

:Repeated measures and multivariate outcomes are an increasingly common feature of trials. Their joint analysis by means of random effects and latent variable models is appealing but patterns of heterogeneity in outcome profile may not conform to standard multivariate normal assumptions. In addition, there is much interest in both allowing for and identifying sub-groups of patients who vary in treatment responsiveness. We review methods based on discrete random effects distributions and mixture models for application in this field.

journal_name

Stat Methods Med Res

authors

Pickles A,Croudace T

doi

10.1177/0962280209105016

subject

Has Abstract

pub_date

2010-06-01 00:00:00

pages

271-89

issue

3

eissn

0962-2802

issn

1477-0334

pii

0962280209105016

journal_volume

19

pub_type

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