Suppose X and Y are binary exposure and outcome variables, and we have full knowledge of the distribution of Y, given application of X. We are interested in assessing whether an outcome in some case is due to the exposure. This "probability of causation" is of interest in comparative historical...

Recent work by Reiss and Ogden provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross-validation (GCV) for smoothing parameter selection in semiparametric regression. However, existing REML or marginal likelihood (ML) based methods for...

Estimates of HIV prevalence are important for policy in order to establish the health status of a country's population, to evaluate the effectiveness of population-based interventions and campaigns, to identify the most at risk members of the population, and to target those most in need of...