Bayesian versus Frequentist Estimation for SEM: A Systematic Review
The Performance of Maximum Likelihood and Bayesian Estimation With Small and Unbalanced Samples in a Latent Growth Model is compared in a simulation study
Small Sample Size Solutions: A Guide for Applied Researchers and Practitioners.
This unique resource provides guidelines and tools for implementing solutions to issues that arise in small sample research, illustrating statistical methods that allow researchers to apply the optimal statistical model for their research question when the sample is too small.
Predicting a Distal Outcome Variable From a Latent Growth Model
The aim of the current simulation study is to examine the performance of an LGM with a continuous distal outcome under maximum likelihood (ML) and Bayesian estimation with default and informative priors, under varying sample sizes, effect sizes and slope variance values.
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: