[R] Regression model
r.turner at auckland.ac.nz
Fri Nov 22 01:42:52 CET 2013
(1) Is this homework? (This list doesn't do homework for people!)
(Animals maybe, but not people! :-) )
(2) Your question isn't really an R question but rather a
question. It is possible that you might get some insight from Frank
"Regression Modelling Strategies" (Springer, 2001).
On 11/22/13 12:52, srecko joksimovic wrote:
> I'm trying to fit regression model, but there is something wrong with it.
> The dataset contains 85 observations for 85 students.Those observations are
> counts of several actions, and dependent variable is final score. More
> precisely, I have 5 IV and one DV. I'm trying to build regression model to
> check whether those variables can predict the final score.
> I'm attaching output of several steps, but I tried to following procedure:
> - build model with only those two variables
> - summary shows that non of them is significant predictor of the final
> - test for multicollinearity revealed tolerance below 0.2 (potential
> - build two new models having as a predictor only one of those values
> - both models show that variable used for the model is significant
> predictor. Separately they are significant, together not. Probably
> multicollinearity problem, but...
> - as I keep adding other variables to one or the other model, Multiple
> R-squared slightly increases.
> - I tried to compare different models using anova, but non of them seems to
> be better.
> How to determine which model is better?
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