Michael Dykes wrote:
I have a project due in my Linear Regression class re: regression on a data
set & my professor gave us a hint that there were *exactly *2 sig
interactions. The data set is attached. We have to find which predictors are
significant, & which 2 interactions are sig. Also, I nedd some guidance for
this & selecting the best model. I tried the `full' model, that being:
z=lm(y~x1+x2+x3+x4+x1*x2+x2*x3...+x3*x4). I then ran an anova(z), &
summary(z). My R^2 & R^2_a were *really* low. I am not sure how to do PRESS,
AIC & Cp in R yet though. Any help would be appreciated.
Michael this is not really the place for help on homework other than
perhaps on technical roadblocks. Note that the strategy you are being
told to follow is one whose statistical properties have been severely
criticized in the statistical literature. Only with a very high signal
to noise ratio (e.g., high true R^2) can torturing data lead to a
confession to something other than what the analyst wants to hear. I
suppose that in simulated data there is a "true" model out there waiting
to be found, but beware of using this approach with real data with low
signal to noise ratios.
Frank
--
Frank E Harrell Jr Professor and Chairman School of Medicine
Department of Biostatistics Vanderbilt University
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