Balancing Type I error and power in linear mixed models
Abstract
Linear mixed-effects models have increasingly replaced mixed-model analyses of variance for statistical inference in factorial psycholinguistic experiments. Although LMMs have many advantages over ANOVA, like ANOVAs, setting them up for data analysis also requires some care. One simple option, when numerically possible, is to fit the full variance-covariance structure of random effects (the maximal model; Barr, Levy, Scheepers & Tily, 2013),...
Paper Details
Title
Balancing Type I error and power in linear mixed models
Published Date
Jun 1, 2017
Volume
94
Pages
305 - 315
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