Sample size calculations for studies with correlated observations.
Correlated data occur frequently in biomedical research. Examples include longitudinal studies, family studies, and ophthalmologic studies. In this paper, we present a method to compute sample sizes and statistical powers for studies involving correlated observations. This is a multivariate extension of the work by Self and Mauritsen (1988, Biometrics 44, 79-86), who derived a sample size and power formula for generalized linear models based on the score statistic. For correlated data, we appeal to a statistic based on the generalized estimating equation method (Liang and Zeger, 1986, Biometrika 73, 13-22). We highlight the additional assumptions needed to deal with correlated data. Some special cases that are commonly seen in practice are discussed, followed by simulation studies.
Liu
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Merck Research Laboratories, Blue Bell, Pennsylvania 19422, USA.
Liang
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D001699:Biometry / Q000379:methods; D005190:Family; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D009010:Monte Carlo Method; D009885:Ophthalmology / Q000379:methods; D012044:Regression Analysis; D012107:Research Design