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American Journal of Epidemiology Vol. 127, No. 5: 1064-1070
Copyright © 1988 by The Johns Hopkins University School of Hygiene and Public Health

research-article

ESTIMATION OF SAMPLE SIZES IN CASE-CONTROL STUDIES WITH MULTIPLE CONTROLS PER CASE: DICHOTOMOUS DATA1

KUNG-JONG LUI

Reprint requests to Dr. K.-J. Lui, Centers for Disease Control, Koger, Room 1055, 1600 Clifton Road, N.E., Atlanta, GA 30333

In planning case-control studies with matched sets, the calculation of exact sample sizes is difficult, because this calculation depends on some nuisance parameters that are usually unknown in practice. Using the Pitman efficiency of Miettinen's test relative to McNemar's test, Schlesselman and Stolley (Case-control studies: design, conduct, analysis. Oxford: Oxford University Press, 1982:144–70) derived an approximate sample size formula which requires the assumption that the difference in exposure rates between cases and controls is small. Furthermore, on the basis of an assumption similar to that used in Schlesselman and Stolley's approach, Taylor (Stat Med 1986;5:29–36) proposed another approximation formula. In this paper, an alternative and explicit formula that does not require the exposure difference to be small between case and control groups has been derived. Monte Carlo studies are given for comparing the accuracy of these three procedures. The results indicate that when odds ratios of exposure between cases and controls are small (≤4) and there is more than one matched control per case, the formula derived in this paper seems to be the best. When odds ratios are large (≥5), however, Taylor's more conservative estimate is recommended, unless the exposure prevalence in the general population is large (0.9).

retrospective studies; statistics

1Division of Viral Diseases, Center for Infectious Diseases, Centers for Disease Control, Atlanta, GA.


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[Abstract] [PDF]


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