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