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The cave of Shadows. Addressing the human factor with generalized additive mixed models
Harald Baayen, Shravan Vasishth, Douglas Bates +1
Generalized additive mixed models are introduced as an extension of the generalized linear mixed model which makes it possible to deal with temporal autocorrelational structure in…
Balancing Type I Error and Power in Linear Mixed Models
Hannes Matuschek, Reinhold Kliegl, Shravan Vasishth +2
Linear mixed-effects models have increasingly replaced mixed-model analyses of variance for statistical inference in factorial psycholinguistic experiments. Although LMMs have many…
Bayesian linear mixed models using Stan: A tutorial for psychologists, linguists, and cognitive scientists
Tanner Sorensen, Shravan Vasishth
With the arrival of the R packages nlme and lme4, linear mixed models (LMMs) have come to be widely used in experimentally-driven areas like psychology, linguistics, and cognitive…
Parsimonious Mixed Models
Douglas Bates, Reinhold Kliegl, Shravan Vasishth +1
The analysis of experimental data with mixed-effects models requires decisions about the specification of the appropriate random-effects structure. Recently, Barr, Levy, Scheepers,…