Hierarchical Regression Flashcards
What is hierarchical regression?
When predictors are entered sequentially in a pre-specified order
How is each predictor evaluated in a hierarchical regression?
In terms of what it adds to the predictor at its point of entry, beyond the variance accounted for in earlier steps
Which predictor will include the shared variance between all predictors in a hierarchical regression?
The predictor entered at step 1
What is the usual order of entering predictors in a hierarchical regression?
- Control variances to partial out their effects (similar to ANCOVA)
- Build a sequential model according to theory
What does R^2 tell us in hierarchical regression?
What is in the full model - the total variance explained by all the predictors
What does R^2 change tell us in hierarchical regression?
The increase in R^2 at each step - the criterion’s unique variance over and above what was accounted for in previous steps
How do you calculate R^2 change?
R^2f - R^2r
Full model - reduced model
What is df Fchange?
Pf - Pr
Predictors in the full model - predictors in the reduced model
What is df error in hierarchical regression?
N - Pf - 1
