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This elaboration outcome increases confidence that the original relationship is nonspurious.
In this elaboration outcome, the control variable is intervening and there is no association in either partial table.
Two or more independent variables in a multiple regression are highly correlated with one another.
Refer to the random processes in a statistical model.
In elaboration analysis, this controls for the extraneous variable.
The association between two variables when no other variable is controlled.
Multivariate analysis involving three-variable contingency tables.
Shows the effect of X on Y while controlling for all other independent variables in a multiple regression analysis.
Simultaneously controls for the effects of several independent variables.
X → T → Y indicates that X has an ________ on Y.
In this elaboration outcome, an antecedent variable creates a spurious association between X and Y.
Produced by omitting important variables from a statistical model.