A GOODNESS-OF-FIT APPROACH TO INFERENCE PROCEDURES FOR THE KAPPA-STATISTIC - CONFIDENCE-INTERVAL CONSTRUCTION, SIGNIFICANCE-TESTING AND SAMPLE-SIZE ESTIMATION
A GOODNESS-OF-FIT APPROACH TO INFERENCE PROCEDURES FOR THE KAPPA-STATISTIC - CONFIDENCE-INTERVAL CONSTRUCTION, SIGNIFICANCE-TESTING AND SAMPLE-SIZE ESTIMATION
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DOI：
10.1002/sim.4780111109
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发表时间：
1992-08-01
影响因子：
2
通讯作者：
ELIASZIW, M
中科院分区：
文献类型：
--
作者：
DONNER, A;ELIASZIW, M
我们提出了一个新的程序来构建一个置信区间的kappa统计量的情况下，两个评分员和一个二分的结果。该程序是基于卡方拟合优度检验，适用于经常用于聚类二进制数据的模型。该程序提供的覆盖水平在尺寸较小的样本中比其他程序所需的覆盖水平更准确。该程序也可用于显著性检验和相应样本量要求的规划。
We propose a new procedure for constructing a confidence interval about the kappa statistic in the case of two raters and a dichotomous outcome. The procedure is based on a chi-square goodness-of-fit test as applied to a model frequently used for clustered binary data. The procedure provides coverage levels that are accurate in samples of smaller size than those required for other procedures. The procedure also has use for significance-testing and the planning of corresponding sample size requirements.