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)
