CT appearances of hydatid disease at various locations

Hydatid disease has characteristic imaging features on CT, which allow accurate preoperative diagnosis in most cases. However, when it occurs at unusual locations the diagnosis is often difficult, especially as the imaging appearance varies at different sites. In this article we have presented a pictorial review of the CT features of disease due to Echinococcus granulosus at various sites in the human body.     

Bayesian estimation of a random effects heteroscedastic probit model

Summary Bayesian analysis is given of a random effects binary probit model that allows for heteroscedasticity. Real and simulated examples illustrate the approach and show that ignoring heteroscedasticity when it exists may lead to biased estimates and poor prediction. The computation is carried out by an efficient Markov chain Monte Carlo sampling scheme that generates the parameters in blocks. We use the Bayes factor, cross‐validation of the predictive density, the deviance information criterion and Receiver Operating Characteristic (ROC) curves for model comparison.