Podgor M J, Gastwirth J L, Mehta C R
National Eye Institute, Division of Biometry and Epidemiology, National Institutes of Health, Bethesda, Maryland 20892-2510, USA.
Stat Med. 1996 Oct 15;15(19):2095-105. doi: 10.1002/(SICI)1097-0258(19961015)15:19<2095::AID-SIM349>3.0.CO;2-Y.
Ordered categorical data occur frequently in biomedical research. The linear by linear association test for ordered R x C tables permits the investigator to specify row and column scores for analysis. When an investigator believes that there may be more than one set of reasonable scores or when more than one investigator proposes scores, we need a method to decide upon a single procedure to use. We show how to use efficiency robustness principles to combine tests from two or more sets of scores into one robust test for analysis. This test minimizes the worst possible efficiency loss over all the sets of scores. We illustrate the methodology for the R x C case and, in detail, for the important special 2 x C case.
有序分类数据在生物医学研究中经常出现。有序R×C表的线性与线性关联检验允许研究者指定行和列得分进行分析。当研究者认为可能存在不止一组合理得分时，或者当不止一位研究者提出得分时，我们需要一种方法来确定使用单一的程序。我们展示了如何使用效率稳健性原则将来自两组或更多组得分的检验组合成一个用于分析的稳健检验。该检验在所有得分组中最小化了可能的最差效率损失。我们阐述了R×C情形的方法，并详细说明了重要的特殊2×C情形的方法。
