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A goodness-of-fit test for the random-effects distribution in mixed models
Achmad Efendi1, Reza Drikvandi1, Geert Verbeke1,2
11 Interuniversity Institute for Biostatistics and statistical Bioinformatics, KU Leuven, Leuven, Belgium.
Abstract:
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.
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