Selection Strategy for Covariance Structure of Random Effects in Linear Mixed-effects Models

Selection Strategy for Covariance Structure of Random Effects in Linear Mixed-effects Models

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Article ID: iaor2016662
Volume: 43
Issue: 1
Start Page Number: 275
End Page Number: 291
Publication Date: Mar 2016
Journal: Scandinavian Journal of Statistics
Authors: , , , ,
Keywords: medicine, statistics: distributions
Abstract:

Linear mixed‐effects models are a powerful tool for modelling longitudinal data and are widely used in practice. For a given set of covariates in a linear mixed‐effects model, selecting the covariance structure of random effects is an important problem. In this paper, we develop a joint likelihood‐based selection criterion. Our criterion is the approximately unbiased estimator of the expected Kullback–Leibler information. This criterion is also asymptotically optimal in the sense that for large samples, estimates based on the covariance matrix selected by the criterion minimize the approximate Kullback–Leibler information. Finite sample performance of the proposed method is assessed by simulation experiments. As an illustration, the criterion is applied to a data set from an AIDS clinical trial.

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