Open AccessASSUMPTIONS IN MAKING CAUSAL INFERENCES FROM PART CORRELATIONS, PARTIAL CORRELATIONS AND PARTIAL REGRESSION COEFFICIENTS
Author(s) -
Linn Robert L.,
Werts Charles E.
Publication year - 1969
Publication title -
ets research bulletin series
Language(s) - English
Resource type - Journals
eISSN - 2333-8504
pISSN - 0424-6144
DOI - 10.1002/j.2333-8504.1969.tb00166.x
Subject(s) - spurious relationship , antecedent (behavioral psychology) , partial correlation , variable (mathematics) , mathematics , partial least squares regression , regression analysis , regression , econometrics , linear regression , causality (physics) , statistics , causal model , correlation , psychology , social psychology , physics , mathematical analysis , geometry , quantum mechanics
Given a linear model and that X is antecedent to Y, a third variable, W, which is antecedent to both X and Y, is often used as a control variable to remove any spurious association between X and Y. Four different methods that have been used as measures of the “influence” of X on Y are described. The implicit assumptions that are made in using each of these methods to make causal inferences are stated and compared.