Latent mixture models for multivariate and longitudinal outcomes

TY - JOUR

T1 - Latent mixture models for multivariate and longitudinal outcomes

AU - Pickles, Andrew

AU - Croudace, Tim

PY - 2010/6

Y1 - 2010/6

N2 - Repeated measures and multivariate outcomes are all 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.

AB - Repeated measures and multivariate outcomes are all 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.

U2 - 10.1177/0962280208105016

DO - 10.1177/0962280208105016

M3 - Article

SN - 0962-2802

VL - 19

SP - 271

EP - 289

JO - Statistical Methods in Medical Research

JF - Statistical Methods in Medical Research

IS - 3

ER -