Statistical Methods for Small Data
After the publication of our paper Bayesian PTSD-Trajectory Analysis with Informed Priors Based on a Systematic Literature Search and Expert Elicitation in Multivariate Behavioral Research, I was contacted by Scientia whether I was interested in an outreach publication based on our paper. Since I had funding for this…
“Shape sorting” students for special education services?
In this dissertation, we focused on two alternative approaches to evaluate the hypothesis of interest more directly, i.e. informative hypothesis testing and model selection using order-restricted information criteria.
Impressions of the S4-conference
The first edition of the S4-conference (Small Sample Size Solutions) was a big succes! The conference was organized in Utrecht from March 5-8 (2018). There were 110 participants from all over the world (South-Africa, Australia, USA, and many more countries) who enjoyed four days in the lovely…
Bayes with Informed Priors Based on Literature and Expert Elicitation
Bayesian Trajectory Analysis with Informed Priors Based on a Systematic Literature Search and Expert Elicitation in the field of Post Traumatic Stress.
Bayesian PTSD-Trajectory Analysis with Informed Priors
we illustrate how to obtain background information using previous literature in the field of PTSD based on a systematic literature search and by using expert knowledge. Finally, we show how to translate this knowledge into prior distributions and we illustrate how to run a Bayesian LGMM.
Applying guidelines to construct informative priors in small sample research
The current paper demonstrates the usefulness of Bayesian estimation with small samples. In Bayesian estimation, prior information can be included …
Small Sample Size Conference
Researchers often have difficulties collecting enough data to obtain statistical power: when target groups are small, hard to access, or measuring the participants requires prohibitive costs. Such obstacles to collecting data usually lead to a limited data set. Researchers can overcome this through simplifying their…
Improving Transparency and Replication in Bayesian Statistics: The WAMBS-Checklist
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 statistics, our personal experience has led us to believe that naively applying Bayesian methods can be dangerous for at least 3 main reasons:
A Systematic Review of Bayesian Papers in Psychology: The Last 25 Years
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 Bayesian approach to statistics is gaining in popularity.
Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimation
Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation.
Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors
The analysis of small data sets in longitudinal studies can lead to power issues and often suffers from biased parameter values. These issues can be solved by using Bayesian estimation in conjunction with informative prior distributions.