Informative Priors
Photo by Dariusz Sankowski on Pixabay
Informative priors are a useful tool for researchers who (1) want to contribute to cumulative science, (2) need to deal with small samples, (3) want to avoid estimation issues that occur for some parameters with Bayesian default priors. More details on these topics can be found in the list of papers related to this project.
Below you can also find an introductory video that I made for a lecture about informative priors. Enjoy!
Mariëlle Zondervan-Zwijnenburg
Assistant Professor Methodology and Statistics
My ambition is to enable social science researchers to use the best methods to optimally analyze their data and answer their research questions.
Publications
Pushing the Limits: The Performance of Maximum Likelihood and Bayesian Estimation With Small and Unbalanced Samples in a Latent Growth Model
Abstract. Longitudinal developmental research is often focused on patterns of change or growth across different (sub)groups of …
Where do priors come from? Applying guidelines to construct informative priors in small sample research
In this paper we present and apply guidelines to construct informative priors in a multiple group latent growth model. The application was certainly not the ideal situation that methodologists and statisticians often deal with, which made this paper only more valuable for readers that also struggle with real-life data.
Talks
