2.1k citations · 3.3k across the 7 of their papers we have counts for
8 papers
How to capitalize on a priori contrasts in linear (mixed) models: A tutorial
Daniel J. Schad, Shravan Vasishth, Sven Hohenstein +1
Factorial experiments in research on memory, language, and in other areas are often analyzed using analysis of variance (ANOVA). However, for effects with more than one numerator d…
A Semiparametric Model for Bayesian Reader Identification
Ahmed Abdelwahab, Reinhold Kliegl, Niels Landwehr
We study the problem of identifying individuals based on their characteristic gaze patterns during reading of arbitrary text. The motivation for this problem is an unobtrusive biom…
On the Ambiguity of Interaction and Nonlinear Main Effects in a Regime of Dependent Covariates
Hannes Matuschek, Reinhold Kliegl
The analysis of large experimental datasets frequently reveals significant interactions that are difficult to interpret within the theoretical framework guiding the research. Some…
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…
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,…