Output: Hierarchical Model assuming heterogeneous mortalities

Posterior means, posterior standard deviations and 95% credible intervals (Inference->Samples->stats)

Sample path (history)

Posterior probability densities (Inference->Samples->density)

(Further, right click on the figure->Margins-> Special…->Smooth -> change from 0.2 to 0.1-> apply all)

Sample autocorrelation function (Inference->Samples->auto corr)

Running quantile plot (Inference->Samples->quantiles)

Scatter plots (Inference->Correlations…)

Shrinkage Estimates of mortality (Inference-> Compare-> node:B, axis:loge and click on modelfit)

(Further, right-click on the figure, Titles -> x-axis: log(e), y-axis: B)

Boxplot of mortality (Inference-> Compare-> node:lambda and click on boxplot)

(Further, right-click on the figure, Property…-> Margins -> Special…-> check “rank” and uncheck “showbaseline”. Titles -> x-axis: Hospital)

*Hospital 85 has the smallest mortality rate

Posterior predictive analysis. pleft:Pr(ypred[i] =< y[i]). pright: Pr(y.pred[i]>=y[i])

Inference-> Compare-> node:pleft and click on caterpillar)

(Further, right-click on the figure, Property…-> Margins -> Special…-> check “rank” and showbaseline:0.05)

Inference-> Compare-> node:pright and click on caterpillar)

(Further, right-click on the figure, Property…-> Margins -> Special…-> check “rank” and showbaseline:0.05)