Sample size estimation in research with dependent measures and dichotomous outcomes.
I reviewed sample estimation methods for research designs involving nonindependent data and a dichotomous response variable to examine the importance of proper sample size estimation and the need to align methods of sample size estimation with planned methods of statistical analysis. Examples and references to published literature are provided in this article. When the method of sample size estimation is not in concert with the method of planned analysis, poor estimates may result. The effects of multiple measures over time also need to be considered. Proper sample size estimation is often overlooked. Alignment of the sample size estimation method with the planned analysis method, especially in studies involving nonindependent data, will produce appropriate estimates.
Delucchi
Kevin L
KL
Department of Psychiatry, University of California, San Francisco, Box 0984-TRC, 401 Parnassus Ave, San Francisco, CA 94143-0984, USA. kdelucc@itsa.ucsf.edu
D003198:Computer Simulation; D016001:Confidence Intervals; D003430:Cross-Sectional Studies; D015340:Epidemiologic Research Design; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D015980:Public Health Practice; D018401:Sample Size; D012680:Sensitivity and Specificity