Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/11202
Title: The impact of a misspecified random-effects distribution on the estimation and the performance of inferential procedures in generalized linear mixed models (vol 27, pg 3125, 2008)
Authors: LITIERE, Saskia 
ALONSO ABAD, Ariel 
MOLENBERGHS, Geert 
Issue Date: 2010
Publisher: JOHN WILEY & SONS LTD
Source: STATISTICS IN MEDICINE, 29 (20). p. 2166-2168
Abstract: Estimation in generalized linear mixed models is often based on maximum likelihood theory, assuming that the underlying probability model is correctly specified. However, the validity of this assumption is sometimes difficult to verify. In this paper we study, through simulations, the impact of misspecifying the random-effects distribution on the estimation and hypothesis testing in generalized linear mixed model. It is shown that the maximum likelihood estimators are inconsistent in the presence of misspecification. The bias induced in the mean structure parameters is generally small, as far as the variability of the underlying random-effects is very small as well. However, the estimates of this variability are always severely biased. Given that the variance components are the only tool to study the variability of the true distribution, it is difficult to assess whether problems in the estimation of the mean structure occur. The Type I error rate and the power of the commonly used inferential procedures are also severely affected. The situation is aggrevated if more than one random effect is included in the model. Further, we propose to deal with possible misspecification by way of sensitivity analysis, considering several random-effects distributions. All the results are illustrated using data from a clinical trial in schizophrenia.
Notes: [Litiere, S.; Alonso, A.; Molenberghs, G.] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. [Molenberghs, G.] Katholieke Univ Leuven, Leuven, Belgium.
Keywords: consistency; heterogeneity model; Kullback-Leibler Information Criterion; non-normal random effects; power; type I error
Document URI: http://hdl.handle.net/1942/11202
ISSN: 0277-6715
e-ISSN: 1097-0258
DOI: 10.1002/sim.3908
ISI #: 000281472800009
Rights: Copyright © 2010 John Wiley & Sons, Ltd.
Category: M
Type: Journal Contribution
Appears in Collections:Research publications

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