Abstract:
: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. The method is applied to physical activity data, which uses a wearable accelerometer device to measure daily movement and energy expenditure information. Our approach is also evaluated by a simulation study.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Li H,Zhang Y,Carroll RJ,Keadle SK,Sampson JN,Matthews CEdoi
10.1002/sim.7401subject
Has Abstractpub_date
2017-11-10 00:00:00pages
4028-4040issue
25eissn
0277-6715issn
1097-0258journal_volume
36pub_type
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