My name is Joris Mulder. I work as an assistant professor at the Department of Methodology and Statistics at Tilburg University, the Netherlands. My research focuses on the development of Bayesian statistical methods for social science applications. In particular, I am interested in testing complex hypotheses with equality and order constraints on the parameters of interest, specifying prior distributions for model parameters (objective, subjective, default), and developing efficient computational techniques for Bayesian data analysis. If you want to share your ideas or thoughts or if you have any questions feel free to email me: j [dot] mulder3 [at] tilburguniversity [dot] edu.
As part of my PhD I wrote a software program called BIEMS (Bayesian inequality and equality constrained model selection; Mulder et al., 2012) which can be used for testing hypotheses with multiple inequality/order constraints (<, >) and equality constraints (=) on the parameters of interest.
In 2013 I received a personal Veni grant by the Netherlands Organization for Scientific Research (NWO). In this project I will extend my work by developing methods for testing complex constraints on different types of correlation coefficients, such as partial correlations, intraclass correlations, and network autocorrelations. Recently I developed the program BOCOR for testing order constraints on bivariate correlations (Mulder, 2016). Soon methods will be ready for testing hypotheses with equality and order constraints on partial, bivariate, and polychoric correlations (among others), as well as Bayesian procedures for testing network autocorrelations (Dittrich, Leenders, & Mulder, in prep.), and Bayes factors tests for intraclass correlations (Mulder & Fox, in prep.).