Browner W S, Newman T B
Department of Medicine, Veterans Administration Medical Center, San Francisco 94121.
Am J Public Health. 1989 Sep;79(9):1289-94. doi: 10.2105/ajph.79.9.1289.
Most methods for calculating sample size use the relative risk (RR) to indicate the strength of the association between exposure and disease. For measuring the public health importance of a possible association, the population attributable fraction (PAF)--the proportion of disease incidence in a population that is attributable to an exposure--is more appropriate. We determined sample size and power for detecting a specified PAF in both cohort and case-control studies and compared the results with those obtained using conventional estimates based on the relative risk. When an exposure is rare, a study that has little power to detect a small RR often has adequate power to detect a small PAF. On the other hand, for common exposures, even a relatively large study may have inadequate power to detect a small PAF. These comparisons emphasize the importance of selecting the most pertinent measure of association, either relative risk or population attributable fraction, when calculating power and sample size.
大多数计算样本量的方法使用相对风险（RR）来表明暴露与疾病之间关联的强度。对于衡量一种可能关联的公共卫生重要性而言，人群归因分数（PAF）——即人群中疾病发病率可归因于某种暴露的比例——更为合适。我们确定了队列研究和病例对照研究中检测特定PAF的样本量和检验效能，并将结果与使用基于相对风险的传统估计值所获得的结果进行比较。当一种暴露罕见时，一项检测小RR能力不足的研究往往有足够的能力检测小PAF。另一方面，对于常见暴露，即使是规模相对较大的研究检测小PAF的能力也可能不足。这些比较强调了在计算检验效能和样本量时选择最相关的关联度量指标（相对风险或人群归因分数）的重要性。
