Bodian C A
Department of Biomathematical Sciences, Mount Sinai Medical Center, New York, New York 10029.
Biometrics. 1994 Mar;50(1):183-93.
Several sampling designs for assessing agreement between two binary classifications on each of n subjects lead to data arrayed in a four-fold table. Following Kraemer's (1979, Psychometrika 44, 461-472) approach, population models are described for binary data analogous to quantitative data models for a one-way random design, a two-way mixed design, and a two-way random design. For each of these models, parameters representing intraclass correlation are defined, and two estimators are proposed, one from constructing ANOVA-type tables for binary data, and one by the method of maximum likelihood. The maximum likelihood estimator of intraclass correlation for the two-way mixed design is the same as the phi coefficient (Chedzoy, 1985, in Encyclopedia of Statistical Sciences, Vol. 6, New York: Wiley). For moderately large samples, the ANOVA estimator for the two-way random design approximates Cohen's (1960, Psychological Measurement 20, 37-46) kappa statistic. Comparisons among the estimators indicate very little difference in values for tables with marginal symmetry. Differences among the estimators increase with increasing marginal asymmetry, and with average prevalence approaching .50.
在n个受试者中,有几种用于评估两种二元分类之间一致性的抽样设计,会得到排列成四格表的数据。按照克雷默(1979年,《心理测量学》第44卷,第461 - 472页)的方法,针对二元数据描述了总体模型,类似于单向随机设计、双向混合设计和双向随机设计的定量数据模型。对于这些模型中的每一个,都定义了表示组内相关的参数,并提出了两个估计量,一个是通过构建二元数据的方差分析表类型,另一个是通过最大似然法。双向混合设计的组内相关的最大似然估计量与phi系数相同(切佐伊,1985年,《统计科学百科全书》第6卷,纽约:威利出版社)。对于中等大小的样本,双向随机设计的方差分析估计量近似于科恩(1960年,《心理测量》第20卷,第37 - 46页)的kappa统计量。估计量之间的比较表明,对于具有边际对称性的表格,其值差异很小。随着边际不对称性的增加以及平均患病率接近0.50,估计量之间的差异会增大。