The Decomposability and Monotonicity of Pearson's Chi-Square for Collapsed Contingency Tables with Applications
将列联表的皮尔逊卡方统计量分解为多个非负分量之和，证明合并行或列后统计量不会增大，并应用于准独立性和准齐性检验，为同时检验提供一致方法。
Abstract The Pearson chi-square statistic for a contingency table is decomposed into a sum of components. Each component involves the Pearson chi-square statistic for tables that are formed by collapsing (i.e., combining) rows and/or columns of the original table. Since the terms in the decomposition are necessarily nonnegative, this leads to a monotonicity in the statistic; the Pearson chi-square value for any table N is never smaller than the corresponding values for tables formed by collapsing N. The decomposition is shown to be applicable to tests for quasi-independence or quasi-homogeneity, and the monotonicity provides a coherent simultaneous test procedure. The setting for the proofs provides a probabilistic interpretation for the Pearson chi-square statistic and suggests future areas of research.