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When the outcome of interest is binary, the most general tool for the analysis of matched data is conditional logistic regression as it handles strata of arbitrary size and continuous or binary treatments (predictors) and can control for covariates. In particular cases, simpler tests like paired difference test, McNemar test and Cochran-Mantel-Haenszel test are available.

When the outcome of interest is binary, the most general tool for the analysis of matched data is conditional logistic regression as it handles strata of arbitrary size and continuous or binary treatments (predictors) and can control for covariates. In particular cases, simpler tests like paired difference test, McNemar test and Cochran-Mantel-Haenszel test are available.

当感兴趣的结果是二进制的时候，分析匹配数据最常用的工具是条件 Logit模型，因为它可以处理任意大小的层次和连续或二进制处理(谓词) ，并且可以控制协变量。在特定情况下，可以使用配对差异检验、 McNemar 检验和 cochran-mantel-haenzel 检验等更简单的检验。

当感兴趣的结果是二元变量时，分析匹配数据最常用的工具是条件Logistic回归模型，因为它可以处理'''<font color="#32cd32"> 任意大小的层次和连续或二元处理变量(自变量) 【strata of arbitrary size and continuous or binary treatments (predictors)】</font>''' ，并且可以控制协变量。在特定情况下，可以使用'''<font color="#32cd32"> 配对差异检验【paired difference test】 </font>'''、 McNemar 检验和 Cochran-Mantel-Haenzel 检验等更简单的检验。