Dibyen Majumdar : Efficient Crossover Designs under Subject Dropout

Posted by , part of the Statistics and Data Science Seminar.

At

Nov. 17, 2010, 3 p.m.

In

SEO 636

Abstract

Crossover studies are used in different areas of statistical applications and there is a substantial literature that focus on identifying and constructing efficient designs for these studies. However, even well-designed crossover studies often lose their statistical properties if subjects drop out before the end of the study. We will explore the problem of subject dropout and the effect on properties of the design, and search for efficient designs that are robust to subject dropout.