Sample size calculation for time-averaged differences in the presence of missing data.

Contemporary Clinical Trials
Song Zhang, Chul Ahn

Abstract

Sample size calculations based on two-sample comparisons of slopes in repeated measurements have been reported by many investigators. In contrast, the literature has paid relatively little attention to the sample size calculations for time-averaged differences in the presence of missing data in repeated measurement studies. Diggle et al. (2002) provided a sample size formula detecting time-averaged differences for continuous outcomes in repeated measurement studies assuming no missing data and the compound symmetry (CS) correlation structure among outcomes from the same subject. In this paper we extend Diggle et al.'s timeaveraged difference sample size formula by allowing missing data and various correlation structures. We propose to use the generalized estimating equation (GEE) method to compare the time-averaged differences in repeatedmeasurement studies and introduce a closed form formula for sample size and power. Simulation studies were conducted to investigate the performance of GEE sample size formula with small sample sizes, a damped exponential family of correlation structures and missing data. The proposed sample size formula is illustrated using a clinical trial example.

References

Sep 1, 1994·Journal of the American Geriatrics Society·W S Aronow, C Ahn
Oct 23, 2002·Archives of Disease in Childhood·L Diggle, J Deeks
Jan 19, 2011·Contemporary Clinical Trials·Song Zhang, Chul Ahn

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Citations

Nov 28, 2012·Computational Statistics & Data Analysis·Song Zhang, Chul Ahn
Sep 30, 2015·Contemporary Clinical Trials·Song ZhangChul Ahn
Sep 25, 2018·Radiation Protection Dosimetry·L O'HoraL Rainford
Aug 26, 2015·Statistical Methods in Medical Research·Hong ZhuChul Ahn
Jun 13, 2017·Communications in Statistics: Theory and Methods·Ying LouChul Ahn

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