This supplemental material section contains a robustness analysis where we examined the posterior estimate's sensitivity to choice of priors. In addition, we include a number of tables and figures to supplement our report. RobustnessWe examined the robustness of our Bayesian model by checking the extent to which our marginal posterior estimates depend on the specification of prior distribution parameters. Specifically, we re-estimated the model using significantly more diffuse normally distributed prior distributions by increasing the variance parameter by a factor of 100 in equations 10 to 14. We again ran the sampler in WinBUGS using the same MCMC specifications and computed marginal posterior estimates. Marginal posterior estimates are depicted in Figures