When we have a large number of possible independent variables that we want to explore, and we want to find a smaller set of these variables to use in predicting the dependent variable, eliminating other variables that add only an insignificant or trivial amount of explained variation in the dependent variable beyond the smaller set, we should use the hierarchical multiple regression method.

Question

Quizplus · Accepted Answer

Hierarchical multiple regression is used to assess the incremental value of predictors added sequentially in blocks, not primarily for reducing a large set of variables. Techniques like stepwise regression, principal component analysis, or regularization methods (e.g., LASSO) are more suited for reducing a large number of variables to a smaller set by eliminating insignificant predictors.

When We Have a Large Number of Possible Independent Variables