52 citations · 167 across the 19 of their papers we have counts for
11 papers · 1 filter
Approximating Bayesian leave-one-group-out cross-validation
Anna Elisabeth Riha, Svenja Jedhoff, Paul-Christian Bürkner +1
When data are grouped, hierarchical or multilevel models are commonly used to account for group-level variation with group-specific parameters. Leave-one-group-out cross-validation…
Simulation-based validation of Bayes factor computation
Martin Modrák, Sebastian Stroppel, Paul-Christian Bürkner
We propose and evaluate two methods that validate the computation of Bayes factors: one based on an improved variant of simulation-based calibration checking (SBC) and one based on…
Efficient Uncertainty Propagation in Bayesian Two-Step Procedures
Svenja Jedhoff, Hadi Kutabi, Anne Meyer +1
Bayesian inference provides a principled framework for probabilistic reasoning. If inference is performed in two steps, uncertainty propagation plays a crucial role in accounting f…
Gaussian distributional structural equation models: A framework for modeling latent heteroscedasticity
Luna Fazio, Paul-Christian Bürkner
Accounting for the complexity of psychological theories requires methods that can predict not only changes in the means of latent variables -- such as personality factors, creativi…
DGP-LVM: Derivative Gaussian process latent variable models
Soham Mukherjee, Manfred Claassen, Paul-Christian Bürkner
We develop a framework for derivative Gaussian process latent variable models (DGP-LVMs) that can handle multi-dimensional output data using modified derivative covariance function…
Optimal design of the Wilcoxon-Mann-Whitney-test
Paul-Christian Bürkner, Philipp Doebler, Heinz Holling
In scientific research, many hypotheses relate to the comparison of two independent groups. Usually, it is of interest to use a design (i.e., the allocation of sample sizes and…
Testing for Publication Bias in Diagnostic Meta-Analysis: A Simulation Study
Paul-Christian Bürkner, Philipp Doebler
The present study investigates the performance of several statistical tests to detect publication bias in diagnostic meta-analysis by means of simulation. While bivariate models sh…
Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity
Martin Modrák, Angie H. Moon, Shinyoung Kim +5
Simulation-based calibration checking (SBC) is a practical method to validate computationally-derived posterior distributions or their approximations. In this paper, we introduce a…
Prediction can be safely used as a proxy for explanation in causally consistent Bayesian generalized linear models
Maximilian Scholz, Paul-Christian Bürkner
Bayesian modeling provides a principled approach to quantifying uncertainty in model parameters and model structure and has seen a surge of applications in recent years. Within the…
Workflow Techniques for the Robust Use of Bayes Factors
Daniel J. Schad, Bruno Nicenboim, Paul-Christian Bürkner +2
Inferences about hypotheses are ubiquitous in the cognitive sciences. Bayes factors provide one general way to compare different hypotheses by their compatibility with the observed…
Efficient leave-one-out cross-validation for Bayesian non-factorized normal and Student-t models
Paul-Christian Bürkner, Jonah Gabry, Aki Vehtari
Cross-validation can be used to measure a model's predictive accuracy for the purpose of model comparison, averaging, or selection. Standard leave-one-out cross-validation (LOO-CV)…