School of Mathematics and Statistics, University of New South Wales, Sydney, Australia.
PLoS One. 2013;8(3):e58777. doi: 10.1371/journal.pone.0058777. Epub 2013 Mar 7.
Sample size calculations are an important part of research to balance the use of resources and to avoid undue harm to participants. Effect sizes are an integral part of these calculations and meaningful values are often unknown to the researcher. General recommendations for effect sizes have been proposed for several commonly used statistical procedures. For the analysis of 2×2 tables, recommendations have been given for the correlation coefficient φ for binary data; however, it is well known that φ suffers from poor statistical properties. The odds ratio is not problematic, although recommendations based on objective reasoning do not exist. This paper proposes odds ratio recommendations that are anchored to φ for fixed marginal probabilities. It will further be demonstrated that the marginal assumptions can be relaxed resulting in more general results.
样本量计算是研究的重要组成部分,旨在平衡资源的使用并避免对参与者造成不必要的伤害。效应大小是这些计算的一个组成部分,而研究人员通常不知道有意义的效应大小值。已经为几种常用的统计程序提出了关于效应大小的一般建议。对于 2×2 表的分析,已经为二进制数据的相关系数 φ 提出了建议;然而,众所周知,φ 的统计性质较差。优势比没有问题,尽管不存在基于客观推理的建议。本文提出了基于固定边缘概率的 φ 的优势比建议。进一步表明,可以放宽边缘假设,从而得出更一般的结果。