The Plausible Parameter Space (PPS) Shiny App is designed to help users define their priors in a linear regression with two regression coefficients. Users are asked to specify their plausible parameter space and their expected prior means and uncertainty around these means. The PhD-delay data (Van de Schoot et al., 2013) is used an easy-to-go introduction to Bayesian inference. In this example the linear and quadratic effect of age on PhD-delay are estimated. Users learn about the interaction between a linear and a quadratic effect in the same model, about how to think about plausible parameter spaces, and about specification of normally distributed priors for regression coefficients.
First of all, this app might be a useful tool for your teaching if you would like to familiarize your students with the basic logic of Bayesian inference. Second, feel free to use this material as a template for your own app.
Download the files, open R-studio, install the R-packages, and run the app.
The Shiny app also runs at a server of Utrecht University.
The app is self-explanatory. Users can just follow the 4 steps listed in the left side bar and answer the various questions asked.
Laurent Smeets, Ihnwhi Heo or Rens van de Schoot
To cite the PhD-data: Van de Schoot, R., Yerkes, M.A., Mouw, J.M. & Sonneveld, H. (2013). What Took Them So Long? Explaining PhD Delays among Doctoral Candidates. PLoS One, 8(7): e68839. DOI: http://dx.doi.org/10.1371/journal.pone.0068839
This project was funded by the Netherlands organization for scientific research (NWO);grant number VIDI-452-14-006.