rensvandeschoot/plausible-parameter-space

The Plausible Parameter Space (PPS) Shiny App is designed to help users define their priors in a linear regression with two regression coefficients.

Plausible Parameter Space (PPS) Shiny App

⭐ Purpose

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.

💎 How can you profit from it?

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.

Installation

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.

Usage

The app is self-explanatory. Users can just follow the 4 steps listed in the left side bar and answer the various questions asked.

Contact

Laurent Smeets, Ihnwhi Heo or Rens van de Schoot

Reference

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

Funding

This project was funded by the Netherlands organization for scientific research (NWO);grant number VIDI-452-14-006.