A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.
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ABSTRACT:
SUBMITTER: Li H
PROVIDER: S-EPMC5656438 | biostudies-literature | 2017 Nov
REPOSITORIES: biostudies-literature
Publications
A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.
Li Haocheng H Zhang Yukun Y Carroll Raymond J RJ Keadle Sarah Kozey SK Sampson Joshua N JN Matthews Charles E CE
Statistics in medicine 20170807 25
A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and transform the proposed model into a multivariate linear mixed model framework for estimation and inference. Via an extension to the EM approach, an efficient algorithm is developed to fit the model. ...[more]
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