A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models: The R Package pbkrtest

作者: Ulrich Halekoh , Søren Højsgaard

DOI: 10.18637/JSS.V059.I09

关键词: Sample size determinationMathematical optimizationMean valueMathematicsStructure (category theory)Generalized linear mixed modelApplied mathematicsReduction (complexity)ResidualParametric statisticsR package

摘要: When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic ?2 test. Such tests can, however, be very poor small and moderate sample sizes. The pbkrtest package implements two alternatives such approximate tests: (1) a Kenward-Roger approximation performing F (2) parametric bootstrap methods achieving same goal. implementation focused on models with independent residual errors. In addition describing aspects their implementation, paper also contains several examples comparison various methods.

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