Estimators for longitudinal latent exposure models: examining measurement model assumptions.

ABSTRACT: Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straight

SUBMITTER: Sanchez BN 

PROVIDER: S-EPMC5418122 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature