Author: Rens van de Schoot

Directly evaluating expectations or testing the null hypothesis? Null hypothesis testing versus Bayesian model selection

Researchers in psychology have specific expectations about their theories. These are called informative hypothesis because they contain information about reality. Note that these hypotheses are not necessarily the same as the traditional null and alternative hypothesis.

Testing informative hypotheses in SEM increases power: An illustration contrasting classical hypothesis testing with a parametric bootstrap approach

In the present paper, the application of a parametric bootstrap procedure, as described by van de Schoot, Hoijtink, and Deković (2010), will be applied to demonstrate that a direct test of an informative hypothesis offers more informative results compared to testing traditional null hypotheses against catch-all rivals.

Evaluating expectations about negative emotional states of aggressive boys using Bayesian model selection

Researchers often have expectations about the research outcomes in regard to inequality constraints between, e.g., group means. Consider the example of researchers who investigated the effects of inducing a negative emotional state in aggressive boys.

Prolonged Grief Disorder, depression, and posttraumatic stress-disorder are distinguishable syndromes

This study examined the distinctiveness of symptoms of Prolonged Grief Disorder (PGD), depression, and posttraumatic stress disorder (PTSD). We compared the fit of a one-factor model with the fit of four hierarchical models in which symptoms formed three distinct correlated higher-order dimensions, and PTSD-items were modeled in different ways.