Power Calculations for Matched Case-Control Studies

William D. Dupont

Biometrics · 1988 · 335 citations · 6 references

Concepts

TL;DR

The study discusses how sample size, odds ratio, correlation, and exposure probability interact, illustrated with examples. Power formulas for matched case‑control studies are derived, linking exposure probability, correlation, odds ratio, and error rates, and providing sample‑size calculations for specified odds ratios or desired power. Graphs show that power declines with higher exposure correlation and extreme exposure probabilities, necessitating larger sample sizes to maintain power.

Abstract

Power calculations are derived for matched case-control studies in terms of the probability po of exposure among the control patients, the correlation coefficient phi for exposure between matched case and control patients, and the odds ratio psi for exposure in case and control patients. For given Type I and Type II error probabilities alpha and beta, the odds ratio that can be detected with a given sample size is derived as well as the sample size needed to detect a specified value of the odds ratio. Graphs are presented for paired designs that show the relationship between sample size and power for alpha = .05, beta = .2, and different values of po, phi, and psi. The sample size needed for designs involving M matched control patients can be derived from these graphs by means of a simple equation. These results quantify the loss of power associated with increasing correlation between the exposure status of matched case and control patients. Sample size requirements are also greatly increased for values of po near 0 or 1. The relationship between sample size, psi, phi, and po is discussed and illustrated by examples.

References

6