Causal inference is an important but controversial topic in the
social sciences in that it is difficult to statistically control
for all possible confounding variables. To address this concern,
this monograph introduces a reference distribution of the
confounding that is the product of two dependent correlation
coefficients and illustrates how to use the reference distribution
to investigate the robustness of a cause inference to the impact of
a confounding variable. The methodology discussed in this monograph
would also allow for multiple partial causes in the complex social
phenomena under study, so as to inform causal inferences in the
social sciences from statistical linear models.
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