Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …

This paper is a tribute to researchers who have significantly contributed to improving and
advancing structural equation modeling (SEM). It is, therefore, a brief overview of SEM and …

Latent class analysis (LCA) is a statistical method used to identify unobserved subgroups in
a population with a chosen set of indicators. Given the increasing popularity of LCA, our aim …

Estimating models within the mixture model framework, like latent growth mixture modeling
(LGMM) or latent class growth analysis (LCGA), involves making various decisions …

Although the statistical tools most often used by researchers in the field of psychology over
the last 25 years are based on frequentist statistics, it is often claimed that the alternative …

As Bayesian methods continue to grow in accessibility and popularity, more empirical
studies are turning to Bayesian methods to model small sample data. Bayesian methods do …

Bayesian statistical methods are slowly creeping into all fields of science and are becoming
ever more popular in applied research. Although it is very attractive to use Bayesian …

In small sample contexts, Bayesian estimation is often suggested as a viable alternative to
frequentist estimation, such as maximum likelihood estimation. Our systematic literature …

The current paper highlights a new, interactive Shiny App that can be used to aid in
understanding and teaching the important task of conducting a prior sensitivity analysis …

A Single Cohesive Framework of Tools and Procedures for Psychometrics and Assessment
Bayesian Psychometric Modeling presents a unified Bayesian approach across traditionally …