[open] JASP: Some questions about multiple linear regression
I have some questions about multiple linear regressions in JASP.
My first question is about the difference between the Forward and the Stepwise method for entering predictors in a multiple linear regression. I found the following in the Help documentation:
- Forward: Predictors are entered sequentially based on the criterion specified in "Stepping method criteria".
- Stepwise: Predictors are entered sequentially based on the criterion specified in "Stepping method criteria"; after each step, the least useful predictor is removed.
Does this mean that in a forward model it is theoretically possible to end up with a model containing all variables that were entered in the box
Covariates, whereas with a stepwise model the maximum number of predictors that can be included in the model is the total number of Covariates - 1?
I was also wondering whether someone has advice about which of the four methods (Enter, Forward, Backward or Stepwise) is 'best' for students that are using multiple linear regression for the first time. In JASP, the default is "Enter", does this mean that this is the safest/easiest option?
Also, I found the following discussion on github:
Do I understand correctly that theory-driven entering of predictors is not yet possible, but might be added in the future?
My final question is about interactions. There is no option to include interactions in multiple linear regression analyses yet, is there? As a work-around, if it turns out that some of my students want to test for interactions, could I advise them to manually add a column containing the multiplication of the values from two predictors? Or is there something wrong with this method?
Any help would be very appreciated!!