In many scientific and medical settings, large-scale experiments are generating large quantities of data that lead to inferential problems involving multiple hypotheses. This has led to recent tremendous interest in statistical methods regarding the false discovery rate (FDR). Several authors...

In the wake of the Enron and Worldcom financial scandals that rocked Wall Street in 2002, the US government’s financial regulatory body, the Security and Exchange Commission (SEC) took the unprecedented step in June 2002 of requiring that the chief executives and chief financial officers of...

Current statistical inference problems in genomic data analysis involve parameter estimation for high-dimensional multivariate distributions, with typically unknown and intricate correlation patterns among variables. Addressing these inference questions satisfactorily requires: (i) an intensive...

An important problem in epidemiology and medical research is the estimation of a causal effect of a treatment action at a single point in time on the mean of an outcome within a population defined by strata of some of the observed covariates. Marginal structural models (MSM) are models for...

In van der Laan and Dudoit (2003) we propose and theoretically study a unified loss function based statistical methodology, which provides a road map for estimation and performance assessment. Given a parameter of interest which can be described as the minimizer of the population mean of a loss...