Van Erp, S. (2020). Bayesian Structural Equation Modeling: The Power of the Prior. PhD-thesis.

van Erp, S. (2020). A Tutorial on Bayesian Penalized Regression with Shrinkage Priors for Small Sample Sizes. In R. Van de Schoot & M. Miočević (Eds.), Small Sample Size Solutions: A Guide for Applied Researchers and Practitioners. Routledge.


Van Erp, S., Oberski, D. L., & Mulder, J. (2019). Shrinkage Priors for Bayesian Penalized Regression. Journal of Mathematical Psychology, 89, 31-50. doi:10.1016/ Preprint and code available here.


Van Erp, S., Mulder, J., & Oberski, D. L. (2018). Prior Sensitivity Analysis in Default Bayesian Structural Equation Modeling. Psychological Methods, 23(2), 363-388. doi:10.1037/met0000162. Preprint available here.


Van Erp, S., Verhagen, J., Grasman, R. P. P. P., & Wagenmakers, E.-J. (2017). Estimates of Between-Study Heterogeneity for 705 Meta-Analyses Reported in Psychological Bulletin From 1990-2013. Journal of Open Psychology Data, 5(1), 4. doi:10.5334/jopd.33. Preprint available here.

Gronau, Q. F., Van Erp, S., Heck, D. W., Cesario, J., Jonas, K. J., & Wagenmakers, E.-J. (2017). A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: the case of felt power. Comprehensive Results in Social Psychology, 2(1), 123–138. doi:10.1080/23743603.2017.1326760. Preprint available here.