Work

Effects of correlation and missing data on sample size estimation in longitudinal clinical trials

Year: 2008

Type: article

Abstract: In longitudinal clinical trials, a common objective is to compare the rates of changes in an outcome variable between two treatment groups. Generalized estimating equation (GEE) has been widely used to examine if the rates of changes are significantly different between treatment groups due to its robustness to misspecification of the true correlation structure and randomly missing data. The sample size formula for repeated outcomes is based on the assumption of missing completely at random and a large sample approximation. A simulation study is conducted to investigate the performance of GEE sample size formula with small sample sizes, damped exponential family of correlation structure and non-ignorable missing data.

Source: Pharmaceutical Statistics

DOI: 10.1002/pst.359

Authors: Song Zhang, Chul Ahn

Institution: The University of Texas Southwestern Medical Center

Language: English

Topic: Statistical Methods in Clinical Trials

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Center for Research Resources