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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24136

Title: Diagnosing Misspecification of the Random-Effects Distribution in Mixed Models
Authors: Drikvandi, Reza
Verbeke, Geert
Molenberghs, Geert
Issue Date: 2017
Publisher: WILEY
Citation: BIOMETRICS, 73(1), p. 63-71
Abstract: It is traditionally assumed that the random effects in mixed models follow a multivariate normal distribution, making likelihood-based inferences more feasible theoretically and computationally. However, this assumption does not necessarily hold in practice which may lead to biased and unreliable results. We introduce a novel diagnostic test based on the so-called gradient function proposed by Verbeke and Molenberghs (2013) to assess the random-effects distribution. We establish asymptotic properties of our test and show that, under a correctly specified model, the proposed test statistic converges to a weighted sum of independent chi-squared random variables each with one degree of freedom. The weights, which are eigenvalues of a square matrix, can be easily calculated. We also develop a parametric bootstrap algorithm for small samples. Our strategy can be used to check the adequacy of any distribution for random effects in a wide class of mixed models, including linear mixed models, generalized linear mixed models, and non-linear mixed models, with univariate as well as multivariate random effects. Both asymptotic and bootstrap proposals are evaluated via simulations and a real data analysis of a randomized multicenter study on toenail dermatophyte onychomycosis.
Notes: [Drikvandi, Reza; Verbeke, Geert; Molenberghs, Geert] Katholieke Univ Leuven, I BioStat, Leuven, Belgium. [Drikvandi, Reza] Imperial Coll London, Dept Math, London, England. [Verbeke, Geert; Molenberghs, Geert] Univ Hasselt, I BioStat, Hasselt, Belgium.
URI: http://hdl.handle.net/1942/24136
DOI: 10.1111/biom.12551
ISI #: 000397855900006
ISSN: 0006-341X
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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