36 citations · 60 across the 9 of their papers we have counts for
9 papers
Closed-form approximations of the two-sample Pearson Bayes factor
Thomas J. Faulkenberry
In this paper, I present three closed-form approximations of the two-sample Pearson Bayes factor, a recently developed index of evidential value for data in two-group designs. The…
Computing analytic Bayes factors from summary statistics in repeated-measures designs
Thomas J. Faulkenberry, Keelyn B. Brennan
Bayes factors are an increasingly popular tool for indexing evidence from experiments. For two competing population models, the Bayes factor reflects the relative likelihood of obs…
A note on the normality assumption for Bayesian models of constraint in behavioral individual differences
Thomas J. Faulkenberry
To investigate the structure of individual differences in performance on behavioral tasks, Haaf and Rouder (2017) developed a class of hierarchical Bayesian mixed models with varyi…
The Pearson Bayes factor: An analytic formula for computing evidential value from minimal summary statistics
Thomas J. Faulkenberry
In Bayesian hypothesis testing, evidence for a statistical model is quantified by the Bayes factor, which represents the relative likelihood of observed data under that model compa…
Estimating Bayes factors from minimal summary statistics in repeated measures analysis of variance designs
Thomas J. Faulkenberry
In this paper, I develop a formula for estimating Bayes factors directly from minimal summary statistics produced in repeated measures analysis of variance designs. The formula, wh…
A tutorial on generalizing the default Bayesian t-test via posterior sampling and encompassing priors
Thomas J. Faulkenberry
With the advent of so-called default Bayesian hypothesis tests, scientists in applied fields have gained access to a powerful and principled method for testing hypotheses. However,…
Computing Bayes factors to measure evidence from experiments: An extension of the BIC approximation
Thomas J. Faulkenberry
Bayesian inference affords scientists with powerful tools for testing hypotheses. One of these tools is the Bayes factor, which indexes the extent to which support for one hypothes…
A hierarchical Bayesian model for measuring individual-level and group-level numerical representations
Thomas J. Faulkenberry
A popular method for indexing numerical representations is to compute an individual estimate of a response time effect, such as the SNARC effect or the numerical distance effect. C…
Approximating Bayes factors from minimal ANOVA summaries: An extension of the BIC method
Thomas J. Faulkenberry
In this paper, I extend a method of Masson (2011) to develop an easy-to-use formula for performing Bayesian hypothesis tests from minimal ANOVA summaries.