The paper considers estimating a parameter "&bgr;" that defines an estimating function "U"("y", "x", "&bgr;") for an outcome variable "y" and its covariate "x" when the outcome is missing in some of the observations. We assume that, in addition to the outcome and the covariate, a surrogate outcome...

There is a large literature on methods of analysis for randomized trials with noncompliance which focuses on the effect of treatment on the average outcome. The paper considers evaluating the effect of treatment on the entire distribution and general functions of this effect. For distributional...

The problem of missing response data is ubiquitous in medical and social science studies. In the case of responses that are missing at random (depending on some covariate information), analyses focused only on the complete data may lead to biased results. Various debias methods have been...

Testing the equality of two survival distributions can be difficult in a prevalent cohort study when non-random sampling of subjects is involved. Owing to the biased sampling scheme, the independent censoring assumption is often violated. Although the issues about biased inference caused by...

Recently there has been a surge in econometric and epidemiologic works focusing on estimating average treatment effects under various sets of assumptions. Estimation of average treatment effects in observational studies often requires adjustment for differences in pretreatment variables....