Multiple linear regression/Types

There are several types of MLR, including:

Type	Characteristics
Direct (or Standard)	All IVs are entered simultaneously
Hierarchical	IVs are entered in steps, i.e., some before others Interpret: R2 change, F change
Forward	The software enters IVs one by one until there are no more significant IVs to be entered
Backward	The software removes IVs one by one until there are no more non-significant IVs to removed
Stepwise	A combination of Forward and Backward MLR. Stepwise regression will do the most efficient job of quickly sorting through many IVs and identifying a relatively simple model based only on the statistically significant predictors.

Forward, Backward, and stepwise regression hands the decision-making power over to the computer which should be discouraged for theory-based research.

For more information, see Multiple linear regression I (Lecture)