Multiple linear regression/Types

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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)