1 citations · 2 across the 10 of their papers we have counts for
10 papers
Simulation-Free Bayesian Power and Sample Size Calculations for Bayes Factors in Single-Arm Phase II Trials with Binary Endpoints
Riko Kelter, Kathrin Möllenhoff
Bayes factors provide a coherent Bayesian measure of evidence for competing hypotheses and have recently been used as the basis for single-arm phase II trial designs with binary en…
Optimal sequential two-stage Bayes Factor Design for two-arm clinical Phase II Trials with binary Endpoints
Riko Kelter
Two-arm phase II clinical trials often benefit from an interim analysis that allows early stopping for futility, but Bayesian calibration of such designs is usually based on comput…
Power and Sample Size Calculations for Bayes Factors in two-arm clinical Phase II Trials with binary Endpoints
Riko Kelter
Bayesian sample size calculations in clinical trials usually rely on complex Monte Carlo simulations in practice. Obtaining bounds on Bayesian notions of the false-positive rate an…
The Bayesian optimal two-stage design for clinical phase II trials based on Bayes factors
Riko Kelter, Samuel Pawel
Sequential trial design is an important statistical approach to increase the efficiency of clinical trials. Bayesian sequential trial design relies primarily on conducting a Monte…
Bayesian Power and Sample Size Calculations for Bayes Factors in the Binomial Setting
Riko Kelter, Samuel Pawel
Bayesian design of experiments and sample size calculations usually rely on complex Monte Carlo simulations in practice. Obtaining bounds on Bayesian notions of the false-positive…
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…