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st: multiple regression, r squared and normality of residuals
From
Arti Pandey <[email protected]>
To
[email protected]
Subject
st: multiple regression, r squared and normality of residuals
Date
Tue, 22 Mar 2011 18:11:07 -0700 (PDT)
Hello
I ran multiple regression with in stata using two models;
the first gave an R-squared of .35, p values of all predictors was less than
0.001 except one which was less than 0.05. No. of obs. used was 84,
distribution of residuals was normal.
Then I did a log transform of the dependent variable, r squared went up to .65,
p values for all predictors was 0.001 except the one mentioned above, which is
now 0.06. The residuals were also slightly skewed to the left. No. of obs went
down to 77.
My question is how do I decide between the R squared and distribution of
residuals. Is such a high rise in R squared worth sacrificing no of observations
and normal distribution of residuals for. Since the skew is not very pronounced,
it is tempting to go with the second, but then the regression model might be
wrong.....
Appreciate any help.
Arti
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