Anastasios Tsiatis, Ph.D.

Professor of Statistics

North Carolina State University

Efficient estimation of the mean of a time-lagged response

subject to right censoring

In many clinical trials the endpoint of interest may not be available immediately, but

rather evolves over time. Examples of this are numerous. Survival time is clearly such

an example, but also cost of care, quality adjusted lifetime, or even dichotomous response

such as whether viral load will go below detectable limits after treatment for AIDS

patients, are also examples of time-lagged responses. The lag time may be part of the

biological process or due to administrative delays. Since patient entry is staggered and

follow-up is of limited duration, some of the response variables will be missing due to

censoring of the lag time. We will show how the theory of inverse probability weighting

of complete cases developed by Robbins and Rotnitzky can be used to find consistent

estimators for the mean of a time-lagged variable. We will also show how to use

additional information collected during the study to increase efficiency.