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A note on permutation tests for variance components in multilevel generalized linear mixed models 总被引:2,自引:0,他引:2
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. 相似文献
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Bartlett corrections to likelihood ratio tests 总被引:1,自引:0,他引:1
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