Title: Statistical power calculations for clustered continuous data

Authors: A.T. Galecki, S. Chen, J.A. Faulkner, J. Ashton-Miller, T. Burzykowski

Addresses: 300 NIB, Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology, University of Michigan Medical School, Ann Arbor, MI 48109-2007, USA. ' 300 NIB, Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology, University of Michigan Medical School, Ann Arbor, MI 48109-2007, USA. ' 300 NIB, Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology, University of Michigan Medical School, Ann Arbor, MI 48109-2007, USA. ' 300 NIB, Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology, University of Michigan Medical School, Ann Arbor, MI 48109-2007, USA. ' I-BioStat, Hasselt University; Catholic University of Leuven, Agoralaan 1, B3590 Diepenbeek, Belgium Diepenbeek, Belgium

Abstract: To calculate the sample size for a research study, it is important to take into account several aspects of the study design. In particular, one needs to take into account the hypotheses being tested, the study design, the sampling design, and the method to be used for the analysis. In this paper, we propose a simple method to calculate sample size for clustered continuous data under various scenarios of study design.

Keywords: sample size; clustered continuous data; study design; sampling design; research studies.

DOI: 10.1504/IJKESDP.2009.021983

International Journal of Knowledge Engineering and Soft Data Paradigms, 2009 Vol.1 No.1, pp.40 - 48

Published online: 15 Dec 2008 *

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