A goodness-of-fit test for the random-effects distribution in mixed models

In this paper, we develop a simple diagnostic test for the random-effects distribution in mixed models. The test is based on the gradient function, a graphical tool proposed by Verbeke and Molenberghs to check the impact of assumptions about the random-effects distribution in mixed models on inferen...

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Bibliographic Details
Published in:Statistical methods in medical research 2017-04, Vol.26 (2), p.970-983
Main Authors: Efendi, Achmad, Drikvandi, Reza, Verbeke, Geert, Molenberghs, Geert
Format: Article
Language:English
Subjects:
Biostatistics - methods
Bootstrap method
Computer Simulation
Data Interpretation, Statistical
Databases, Factual - statistics & numerical data
Diagnostic systems
Diagnostic tests
Epilepsy - drug therapy
Foot Dermatoses - drug therapy
Humans
Medical research
Models, Statistical
Onychomycosis - drug therapy
Randomized Controlled Trials as Topic - statistics & numerical data
Simulation
Statistical methods
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Summary:In this paper, we develop a simple diagnostic test for the random-effects distribution in mixed models. The test is based on the gradient function, a graphical tool proposed by Verbeke and Molenberghs to check the impact of assumptions about the random-effects distribution in mixed models on inferences. Inference is conducted through the bootstrap. The proposed test is easy to implement and applicable in a general class of mixed models. The operating characteristics of the test are evaluated in a simulation study, and the method is further illustrated using two real data analyses.
ISSN:0962-2802
1477-0334
DOI:10.1177/0962280214564721