Tests for Homogeneity of Odds Ratio When the Data are Sparse
通过蒙特卡洛实验研究了稀疏数据下2×2列联表比值比同质性的三种检验方法，发现基于对数比值比服从未知分布的得分检验比其他两种更有效。
Three tests for homogeneity of odds ratio for a series of 2 × 2 tables when the data are sparse are studied by means of Monte Carlo experiments. A score test, based on the assumption that the log odds ratios are generated from some unknown distribution, is shown to be more powerful than the other two. The original test of Zelen (1971), later corrected by Halperin, Ware, Byar et al. (1977), is also examined. It tends to be too liberal under the sparse data situation; however, it has approximately the nominal size when there are as many as ten tables with as few as ten observations per table.