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