Configurations of hyperparameter values for informative priors in the Bayesian model [Eqs (11 and 12)].

Here b0 and B0 denote respectively the prior mean vector and precision matrix for the regression coefficients, and c0/2 and d0/2 denote respectively the shape parameter and scale parameter for the inverse Gamma prior on σ2 (the variance of the disturbances). These latter two parameters can be respectively interpreted as indicating the amount of information, and the sum of squared errors, from c0 pseudo-observations, for the inverse Gamma prior on σ2 (the variance of the residuals) [16]. Note that (a) depicts the baseline uninformative priors used in the primary analyses, whereas (b) to (h) illustrate seven alternate priors.