Mullooly J P
Am J Epidemiol. 1987 Jun;125(6):1079-84. doi: 10.1093/oxfordjournals.aje.a114623.
This paper discusses sample sizes for estimation of exposure-specific disease rates for population-based case-control studies. Neutra and Drolette's confidence limits, which are based on the approximate normality of the logarithm of the ratio of independent binomial exposure rates, are used to determine the sample sizes required for precise estimation of exposure-specific disease rates. It is shown that, for large sample sizes, the disease rate in the exposed population is more precisely estimated than the disease rate in the unexposed population when more than 50% of the cases are exposed, and that the converse is true when fewer than 50% of the cases are exposed. Expressions are derived for the optimal case and control sample sizes that ensure the required level of precision and minimize the total study size. The optimum control-to-case ratio is found to be equal to the square root of the exposure odds ratio. The optimum number of cases and the total study size are found to be smaller for precise estimation of the disease rate in the exposed population than for precise estimation of the exposure odds ratio when the disease is rare.
本文讨论了基于人群的病例对照研究中用于估计特定暴露疾病率的样本量。基于独立二项式暴露率之比的对数近似正态性的纽特拉和德罗莱特置信限，用于确定精确估计特定暴露疾病率所需的样本量。结果表明，对于大样本量，当超过50%的病例暴露时，暴露人群中的疾病率比未暴露人群中的疾病率估计得更精确，而当少于50%的病例暴露时，情况则相反。推导了确保所需精度水平并使总研究规模最小化的最佳病例和对照样本量的表达式。发现最佳对照与病例比等于暴露比值比的平方根。当疾病罕见时，精确估计暴露人群中的疾病率所需的最佳病例数和总研究规模比精确估计暴露比值比时要小。
