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Let some subject have a vector of covariates ''X'' (i.e.: conditionally unconfounded), and some '''potential outcomes''' ''r''<sub>0</sub> and ''r''<sub>1</sub> under control and treatment, respectively. Treatment assignment is said to be '''strongly ignorable''' if the potential outcomes are [[statistical independence|independent]] of treatment (''Z'') conditional on background variables ''X''. This can be written compactly as
Let some subject have a vector of covariates ''X'' (i.e.: conditionally unconfounded), and some '''potential outcomes''' ''r''<sub>0</sub> and ''r''<sub>1</sub> under control and treatment, respectively. Treatment assignment is said to be '''strongly ignorable''' if the potential outcomes are [[statistical independence|independent]] of treatment (''Z'') conditional on background variables ''X''. This can be written compactly as
设某个物体有协变量向量''X''（即：条件无混杂），以及一些'''潜在结果‘’‘ ''r''<sub>0</sub>和''r''<sub>1</sub>分别对应着控制和处理两种情况。如果潜在结果在给定背景变量''X''的条件下独立于处理举动（''Z''），则可以说对样本接受处理的指配是'''强可忽略'''的。可简洁表述为
设某个物体有协变量向量''X''（即：条件非混杂变量），以及一些'''潜在结果'''''r''<sub>0</sub>和''r''<sub>1</sub>分别对应着控制和处理两种情况。如果潜在结果在给定背景变量''X''的条件下独立于处理举动（''Z''），则可以说对样本接受处理的指配是'''强可忽略'''的。可简洁表述为
:<math> r_0, r_1 \perp Z \mid X </math>
:<math> r_0, r_1 \perp Z \mid X </math>
这里<math>\perp</math>代表[[statistical independence｜统计独立]].<ref name="Rosenbaum 1983 41–55"/>
这里<math>\perp</math>代表[[statistical independence|统计独立]].<ref name="Rosenbaum 1983 41–55"/>
===Balancing score===
===Balancing score===