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