Code for the ShinyApp to Determine the Plausible Parameter Space for the PhD-delay Data

This 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 the parameters of a regression example. The PhD-delay example has been used in  many easy-to-go introductions to Bayesian inference, e.g, in JASP. In the app priors for the linear and quadratic effect of age on PhD-delay can be determined. 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. More information about the data and the model can be found in Van de Schoot et al. (2013). The App runs on the server of Utrecht University.