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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 | Source: | 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. | Keywords: | Asymptotic distribution; Eigenvalues; Gradient function; Longitudinal data; Parametric bootstrap; Random effects;asymptotic distribution; eigenvalues; gradient function; longitudinal data; parametric bootstrap; random effects | Document URI: | http://hdl.handle.net/1942/24136 | ISSN: | 0006-341X | e-ISSN: | 1541-0420 | DOI: | 10.1111/biom.12551 | ISI #: | 000397855900006 | Rights: | © 2016, The International Biometric Society | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2018 |
Appears in Collections: | Research publications |
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drikvandi2016.pdf Restricted Access | Published version | 245.22 kB | Adobe PDF | View/Open Request a copy |
Paper_FinalVersion.pdf | Peer-reviewed author version | 287.18 kB | Adobe PDF | View/Open |
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