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Simplex Mixed-Effects Models for Longitudinal Proportional Data

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Author Info
ZHENGUO QIU
PETER X.-K. SONG
MING TAN
Abstract

Continuous proportional outcomes are collected from many practical studies, where responses are confined within the unit interval (0,1). Utilizing Barndorff-Nielsen and Jørgensen's simplex distribution, we propose a new type of generalized linear mixed-effects model for longitudinal proportional data, where the expected value of proportion is directly modelled through a logit function of fixed and random effects. We establish statistical inference along the lines of Breslow and Clayton's penalized quasi-likelihood (PQL) and restricted maximum likelihood (REML) in the proposed model. We derive the PQL/REML using the high-order multivariate Laplace approximation, which gives satisfactory estimation of the model parameters. The proposed model and inference are illustrated by simulation studies and a data example. The simulation studies conclude that the fourth order approximate PQL/REML performs satisfactorily. The data example shows that Aitchison's technique of the normal linear mixed model for logit-transformed proportional outcomes is not robust against outliers. Copyright (c) Board of the Foundation of the Scandinavian Journal of Statistics 2008.

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File URL: http://www.blackwell-synergy.com/doi/abs/10.1111/j.1467-9469.2008.00603.x
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Article provided by Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association and Swedish Statistical Association in its journal Scandinavian Journal of Statistics.

Volume (Year): 35 (2008)
Issue (Month): 4 ()
Pages: 577-596
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Handle: RePEc:bla:scjsta:v:35:y:2008:i:4:p:577-596

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