Sample Size Determination for Designing a Strata-Matched Case-Control Study to Detect Multiple Risk Factors

✍ Scribed by Jun-Mo Nam

• Publisher: John Wiley and Sons
• Year: 1997
• Tongue: English
• Weight: 729 KB
• Volume: 39
• Category: Article
• ISSN: 0323-3847
• DOI: 10.1002/bimj.4710390406

✦ Synopsis

Investigations of sample size for planning casecontrol studies have usually been limited to detecting a single factor. In this paper, we investigate sample size for multiple risk factors in strata-matched casecontrol studies. We construct an omnibus statistic for testing M different risk factors based on the jointly sufficient statistics of parameters associated with the risk factors. The statistic is non-iterative, and it reduces to the Cochran statistic when M = 1. The asymptotic power function of the test is a noncentral chi-square with M degrees of free3om and the sample size required for a specific power can be obtained by the inverse relationship. We find that the equal sample allocation is optimum. A Monte Carlo experiment demonstrates that an approximate formula for calculating sample size is satisfactory in typical epidemiologic studies. An approximate sample size obtained using Bonfemni's method for multiple comparisons is much larger than that obtained using the omnibus test. Approximate sample size formulas investigated in this paper using the omnibus test, as well as the individual tests, can be useful in designing case-control studies for detecting multiple risk factors.