5 papers
The Full Bayesian Significance Test and the e-value -- Foundations, theory and application in the cognitive sciences
Riko Kelter, Julio Michael Stern
Hypothesis testing is a central statistical method in psychological research and the cognitive sciences. While the problems of null hypothesis significance testing (NHST) have been…
fbst: An R package for the Full Bayesian Significance Test for testing a sharp null hypothesis against its alternative via the e-value
Riko Kelter
Hypothesis testing is a central statistical method in psychology and the cognitive sciences. However, the problems of null hypothesis significance testing (NHST) and p-values have…
Bayesian model selection in the -open setting -- Approximate posterior inference and probability-proportional-to-size subsampling for efficient large-scale leave-one-out cross-validation
Riko Kelter
Comparison of competing statistical models is an essential part of psychological research. From a Bayesian perspective, various approaches to model comparison and selection have be…
How to choose between different Bayesian posterior indices for hypothesis testing in practice
Riko Kelter
Hypothesis testing is an essential statistical method in psychology and the cognitive sciences. The problems of traditional null hypothesis significance testing (NHST) have been di…
A new Bayesian two-sample t-test for effect size estimation under uncertainty based on a two-component Gaussian mixture with known allocations and the region of practical equivalence
Riko Kelter
Testing differences between a treatment and control group is common practice in biomedical research like randomized controlled trials (RCT). The standard two-sample t-test relies o…