Title: Goodness-of-fit tests in mixed models
Authors: Claeskens, Gerda
Hart, Jeffrey D.
Issue Date: Feb-2009
Publisher: K.U.Leuven - Faculty of Business and Economics
Series Title: FBE Research Report KBI_0902A pages:1-25
Abstract: Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of interest.
Our tests are nonparametric in the sense that they are designed to detect virtually any alternative to normality. In case of rejection of the null hypothesis, the nonparametric estimation method that is used to construct a test provides an estimator of the alternative distribution.
Publication status: published
KU Leuven publication type: IR
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven

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