Sample size and power calculations with correlated binary data

Correlated binary data are common in biomedical studies. Such data can be a nalyzed using Liang and Zeger's generalized estimating equations (GEE) appr oach. An attractive point of the GEE approach is that one can use a misspec ified working correlation matrix, such as the working independence model (i .e., the identity matrix), and draw (asymptotically) valid statistical infe rence by using the so-called robust or sandwich variance estimator. In this article we derive some explicit formulas for sample size and power calcula tions under various common situations. The given formulas are based on usin g the robust variance estimator in GEE. We believe that these formulas will facilitate the practice in planning two-arm clinical trials with correlate d binary outcome data. (C) Elsevier Science Inc. 2001.