No, it's not homework, it's just some initial analysis, but still...
and thanks for recommendation.


On Thu, Nov 21, 2013 at 4:42 PM, Rolf Turner <r.turner@auckland.ac.nz>wrote:

>
> (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
> statistics/linear modelling
> question.  It is possible that you might get some insight from Frank
> Harrel's book
> "Regression Modelling Strategies" (Springer, 2001).
>
>     cheers,
>
>     Rolf Turner
>
>
> On 11/22/13 12:52, srecko joksimovic wrote:
>
>> Hi,
>>
>> 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
>> outcome.
>> - test for multicollinearity revealed tolerance below 0.2 (potential
>> problem)
>> - 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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