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The posterior probability of a null hypothesis given a statistically significant result
Daniel J. Schad, Shravan Vasishth
When researchers carry out a null hypothesis significance test, it is tempting to assume that a statistically significant result lowers Prob(H0), the probability of the null hypoth…
Modelling dependency completion in sentence comprehension as a Bayesian hierarchical mixture process: A case study involving Chinese relative clauses
Shravan Vasishth, Nicolas Chopin, Robin Ryder +1
We present a case-study demonstrating the usefulness of Bayesian hierarchical mixture modelling for investigating cognitive processes. In sentence comprehension, it is widely assum…
Statistical methods for linguistic research: Foundational Ideas - Part II
Bruno Nicenboim, Shravan Vasishth
We provide an introductory review of Bayesian data analytical methods, with a focus on applications for linguistics, psychology, psycholinguistics, and cognitive science. The empir…
Statistical methods for linguistic research: Foundational Ideas - Part I
Shravan Vasishth, Bruno Nicenboim
We present the fundamental ideas underlying statistical hypothesis testing using the frequentist framework. We begin with a simple example that builds up the one-sample t-test from…
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…