A note on permutation tests for variance components in multilevel generalized linear mixed models |
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Authors: | Fitzmaurice Garrett M Lipsitz Stuart R Ibrahim Joseph G |
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Affiliation: | Harvard Medical School, Boston, MA, USA. fitzmaur@hsph.harvard.edu |
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Abstract: | In many applications of generalized linear mixed models to multilevel data, it is of interest to test whether a random effects variance component is zero. It is well known that the usual asymptotic chi-square distribution of the likelihood ratio and score statistics under the null does not necessarily hold. In this note we propose a permutation test, based on randomly permuting the indices associated with a given level of the model, that has the correct Type I error rate under the null. Results from a simulation study suggest that it is more powerful than tests based on mixtures of chi-square distributions. The proposed test is illustrated using data on the familial aggregation of sleep disturbance. |
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Keywords: | Chi-square distribution Likelihood ratio test Score test Variance component |
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