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