Various asymptotic methods of obtaining a confidence interval (CI) for the odds ratio (OR) have been proposed. Surprisingly, insofar as we know, the behavior of these methods has not been evaluated for data proceeding from a cross-sectional study (multinomial sampling), but only for data that originate in a prospective or retrospective study (two independent binomials sampling). The paper evaluates 15 different methods (10 classic ones and 5 new ones). Because the CI is obtained by inversion in θ of the two-tailed test for H_0(θ): OR = (null hypothesis), this paper evaluates the tests for various values of θ, more than the CIs that are obtained. The following statements are valid only for the two-tailed inferences based on 20 ≤ n ≤ 200 and 0.05≤ OR≤20, since these are the limitations of the study. The two best methods are the classic Cornfield chi-squared method for 0.2≤ OR≤5 and, in other cases, the new method of Sterne for chi-squared; but the adjusted likelihood ratio method is a good alternative to the two previous methods, especially to the first when the sample size is large. The three methods require iterative calculations to obtain the CI. If one is looking for methods that are simple to apply (that is, ones that admit a simple, explicit solution), the best option is the Gart logit method for 1/3≤ OR≤3 and, if in other cases, the Agresti logit method. The Cornfield chi-squared and Gart logit methods should not be used outside the specified interval OR. The paper also selects the best methods for realizing the classic independence test (θ = 1).

已经提出了各种获得优势比 ( OR )置信区间 (CI) 的渐近方法。令人惊讶的是，就我们所知，这些方法的行为尚未针对来自横断面研究（多项抽样）的数据进行评估，而仅针对源自前瞻性或回顾性研究（两个独立二项式抽样）的数据进行评估。该论文评估了 15 种不同的方法（10 种经典方法和 5 种新方法）。因为 CI 是通过H _0(θ)的双尾检验的θ反演获得的： OR  =（零假设），本文评估了各种θ值的检验，比获得的 CI 多。以下陈述仅适用于基于 20 ≤ n ≤ 200 和 0.05≤  OR ≤20的双尾推论 ，因为这些是研究的局限性。两种最好的方法是经典的 Cornfield 卡方方法，用于 0.2≤  OR≤5，在其他情况下，卡方的 Sterne 新方法；但是调整后的似然比方法是前两种方法的一个很好的替代方法，尤其是当样本量很大时对第一种方法来说更是如此。这三种方法需要迭代计算才能获得 CI。如果您正在寻找易于应用的方法（即那些承认简单、明确的解决方案的方法），最好的选择是 1/3≤ OR ≤3的 Gart logit 方法 ，如果在其他情况下，则使用 Agresti登录方法。不应在指定区间OR之外使用 Cornfield 卡方和 Gart logit 方法。论文还选择了实现经典独立性测试（θ  =1）的最佳方法。