We consider Bayesian sample size determination using a criterion that utilizes the first two moments of the posterior variance. We study the resulting sample size in dependence on the chosen prior and explore the success rate for bounding the posterior variance below a prescribed limit under the...

The propensity score analysis is one of the most widely used methods for studying the causal treatment effect in observational studies. This paper studies treatment effect estimation with the method of matching weights. This method resembles propensity score matching but offers a number of new...

Purpose – Complementing the importance of adequate relief supplies and transportation capacity in the first two weeks of post-disaster logistics, efficient communication, information sharing, and informed decision making play a crucial yet often underestimated role in reducing wasted material...

The goal of determining which of hundreds of thousands of SNPs are associated with disease poses one of the most challenging multiple testing problems. Using the empirical Bayes approach, the local false discovery rate (LFDR) estimated using popular semiparametric models has enjoyed success in...

A general function to quantify the weight of evidence in a sample of data for one hypothesis over another is derived from the law of likelihood and from a statistical formalization of inference to the best explanation. For a fixed parameter of interest, the resulting weight of evidence that...

The receiver operating characteristic (ROC) curve may be used to evaluate the performance of a biomarker measured on continuous scale to predict disease status or clinical condition. Motivated by the need for novel study designs with better estimation efficiency and reduced study cost, we...

The area under a ROC curve (AUC) and partial area under a ROC curve (pAUC) are important summary measures useful in assessing the accuracy of a diagnostic test or a biomarker in discriminating true disease status. We consider nonparametric estimation of AUC and pAUC under a test-result-dependent...

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently,...

Nonresponse is of particular concern in longitudinal surveys (panels) for several reasons. Cumulative nonresponse over several waves can substantially reduce the proportion of the original sample that remains in the panel. Reduced sample size increases the variance of the estimates and reduces...