2023
Perspectives on the Bayes factor
In this talk I will discuss the Bayes factor: What it is, why (or why not) it should be used, and how to use it. My emphasis will be …
Misuse of Bayesian inference in applied research: Current status and constructive feedback
The use of Bayesian statistics in many scientific fields is a relatively new endeavor. The social sciences, for example, are witnessing …
The Bayes factor: Statistical properties and a diagnosis of its use in applied research
Hypothesis testing is a commonly used inference tool in many research fields. Null hypothesis significance testing (NHST) and its …
2022
Why, When & How to use Bayes Factors
A great franchise comes with a great rivalry: Marvel has Iron Man and Captain America; physics has General Relativity and Quantum …
Introdução à Estatística Bayesiana
Este é um seminário sobre Introdução à Estatística Bayesiana, no âmbito do II Ciclo de Seminários de Bioestatística e Bioinformática …
2021
Open Science
In this talk I will offer a gentle introduction to Open Science: What it is, how it came about, why it is needed, and what it offers.
Different perspectives on the Bayes factor
Here, me and Don van Ravenzwaaij go at it! I argue that a proper use of Bayes factor requires careful judgement and a whole lot of …
Open Science: A must for modern 21st century researchers
In this talk I offer a gentle introduction to Open Science: What it is, how it came about, why it is needed, and what it offers.
2020
An introduction to Bayesian statistics
This is a 2-hour workshop for the Graduate School of Medical Sciences at the UMCG, Groningen. It takes place online (and perhaps also …
Robustness of Bayesian null hypothesis testing under optional stopping
A lot has already been said against the use of optional stopping (i.e., sequential testing) in the frequentist framework. On the other …
2019
Bayesian statistics as a therapy for frequentist problems
This workshop will highlight problems with classical inference tools ($p$-values, CIs) and provide a motivation to use Bayesian …
My current views over the Bayes factor
Null hypothesis significance testing (NHST) has been under scrutiny for decades. The literature shows overwhelming evidence of a large …
From frequentist problems towards Bayesian solutions
The social sciences are undergoing uncertain and exciting days. Perhaps unwillingly, Daryl Bem’s 2011 paper (where he incredibly makes …
Implications of teaching Bayesian statistics to undergraduate psychology students
The current crisis in psychology is claimed to be partly caused by the way we do statistics. This is one of the reasons why it has been …
2018
Elaborating on issues with Bayes factors
Problems with frequentist statistics in general and null hypothesis significance testing in particular are a central issue in …
2017
Three-mode principal component analysis (3MPCA) and item response theory
My talk is divided in two parts. In the first part I will offer an overview over some of my findings in three-way component analysis, …
Unfolding IRT models : Do they always fit when expected?
Item Response Theory (IRT) models are nowadays popular statistical tools in educational, psychological, and clinical assessment. …
Cumulative vs unfolding IRT models : How practice may defy theory
Item response theory (IRT) models are popular statistical tools that allow extracting psychometric information from data. These models …
2014
Detecting misfitting response patterns in educational testing : An empirical application
Person-fit indices were applied to detect inconsistent patterns of correct/incorrect answers to test questions (items) on a high-stakes …
2012
Detecting cheating in unproctored internet testing settings using CUSUMs (and more)
Unproctored Internet Testing (UIT) is becoming more popular in personnel recruitment and selection. A drawback of UIT is that cheating …
2011
Simplicity transformations for three-way arrays with symmetric slices
Tucker three-way PCA and Candecomp/Parafac are two well-known methods of generalizing principal component analysis to three way data. …
2010
2005
A validation methodology in hierarchical clustering
This paper presents a validation methodology in ascending hierarchical clustering. The objects in validation are clustering …
