An alternative REML estimation of covariance matrices in linear mixed models

Erning Li and Mohsen Pourahmadi

Statistics & Probability Letters, 2013, vol. 83, issue 4, 1071-1077

Abstract: We propose a data-driven procedure for modeling covariance matrices in linear mixed-effects models with minimal distributional assumption on the random effects. It is based on elimination of the random effects using a transformation of the response variable. The approach makes it possible for the first time to disentangle the covariance matrices and model them separately. The performance of the proposed method is assessed via simulations and real data.

Keywords: Cholesky decomposition; Covariance matrices; Longitudinal data; Mixed models; Restricted or residual maximum likelihood (REML) (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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DOI: 10.1016/j.spl.2012.12.028

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