Design and Analysis of Pre-Post Studies with a Binary Outcome on Partially Overlapping Units

• Activity Number: 92
• Type: Invited
• Date/Time: Sunday, August 4, 2013 : 8:30 PM to 10:30 PM
• Sponsor: Korean International Statistical Society
• Author(s): Song Zhang*+ and Jing Cao and Chul Ahn
• Companies: The University of Texas Southwestern Medical Center and Southern Methodist University and The University of Texas Southwestern Medical Center
• Keywords: Clinical trial design ; Binary ; pre-post ; sample size ; dependent

Abstract

Partially overlapping research units in a pre-post study leads to a mixed nature of observed data: paired outcomes from those who contribute complete pairs of observations and independent outcomes from those who contribute incomplete (pre only or post only) observations. It is frequently encountered by practitioners for various reasons. For example, substantial missing data in the pre and post measurements effectively leads to partially overlapping units. It also occurs when researcher conduct random survey in a small community before and after a radio campaign. We examine the limitations of the traditional estimator of the intervention effect. A new hybrid estimator is proposed which we theoretically prove to be more efficient than the traditional estimator under practical conditions. We further derived a closed-form sample size formula to help researchers determine how many subjects need to be enrolled in such studies. Simulation and a real application example are presented