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Topic: Statistics: Model Selection Question (Read 1137 times) |
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william wu
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Statistics: Model Selection Question
« on: Oct 23rd, 2008, 8:53pm » |
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The following question is from Christine:
on Oct 23rd, 2008, 3:38pm, Christine wrote:In multivariate regression, one can compare two models where one model has an additional term by using the F-test. This tests the significance of adding the extra term.
Is there a similar test to compare models of the same number of independent variables (IV), but the last IV different in each model?
R2, adjusted R2, R2 pred, and Mallow's Cp all show a difference, but do not test the significance of this difference. |
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Re: Statistics: Model Selection Question
« Reply #1 on: Oct 23rd, 2008, 9:00pm » |
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You can try Vuong's non nested test. There is a R function for that.
http://rss.acs.unt.edu/Rdoc/library/pscl/html/vuong.html
Plus, why do you need to know if one model is significantly better than the other? Usually, if one model has higher adjusted R^2, or any of the statistics, then you should choose that model to do prediction, right?
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