LEVY, R., & MISLEVY, R. J. (2015). Bayesian Psychometric Modeling. Boca Raton, FL: Chapman And Hall/CRC
In recent years, Bayesian inference has earned its place as a fundamental estimation technique within psychometrics and, more generally, latent variable modeling. The increase in popularity of Bayesian estimation within psychometrics is in part due to computational advances that now make these methods viable for use. In addition, the methodological literature on Bayesian inference within psychometrics has identified this form of estimation as useful for tackling difficult estimation issues for a variety of models. The current review is on a new text illustrating the utility of Bayesian methods within psychometrics. Roy Levy and Robert J. Mislevy’s 2016 book entitled “Bayesian Psychometric Modeling” includes topics ranging from basic explanations to advanced issues embedded in Bayesian estimation of psychometric and latent variable models.
The basic structure of the book (492 pages,...
- Carpenter, R., Gelman, A., Hoffman, M., Lee, D., Goodrich, B., Betancourt, M., Brubaker, M. A., Guo, J., Li, P., & Riddell, A. (2016). Stan: A probabilistic programming language.Journal of Statistical Software.Google Scholar
- Depaoli, S., & van de Schoot, R. (in press). Improving transparency and replication in Bayesian statistics: The WAMBS-checklist. Psychological Methods.Google Scholar
- Kruschke, J. K. (2015). Doing Bayesian analysis: A tutorial with R, Jags, and STAN. San Diego, CA: Academic Press.Google Scholar
- Plummer, M. (2015). JAGS Version 4.0.0 user manual. http://sourceforge.net/projects/mcmc-jags/files/Manuals/4.x/
- Plummer, M., Best, N., Cowles, K., Vines, K., Sarkar, D., Bates, D., Almond, R., & Magnusson, A. (2015). coda: Output analysis and diagnostics for MCMC. R package version 0.18-1.Google Scholar
- Van de Schoot, R., Winter, S., Ryan, O., Zondervan-Zwijnenburg, M., & Depaoli, S. (in press). A systematic review of Bayesian papers in psychology: The last 25 years. Psychological Methods. Google Scholar