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Partial F-test comparing full and reduced regression models

2 messages · James R. Milks, Peter Dalgaard

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Dear all:

I have a regression model that has collinearity problems (between three 
regressor variables).  I need a F-test that will allow me to compare 
between full (with all variables) and partial models (minus 1=< 
variables).  The general F-test formula I'm using is:

F = {[SS(full model) - SS(reduced model)] / (#variables taken out)} / 
MSS(full model)

Unfortunately, the ANOVA table parses the SS and MSS between the 
variables and does not give the statistics for the regression model as 
a whole, otherwise I'd do this by hand.

So, really, I have two questions: 1) Can I just add up all the SS and 
MSS for all the variables to get the model SS and MSS and 2)  Are there 
any functions or packages I can use to calculate the F-statistic?

Thank you for any help you can provide.

Sincerely,
Jim Milks

Graduate Student
Environmental Sciences Ph.D. Program
Wright State University
3640 Colonel Glenn Hwy
Dayton, OH 45435
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Jim Milks <jrclmilks at joimail.com> writes:
Just use anova(model1, model2).

(One potential catch: Make sure that both models are fitted to the
same data set. Missing values in predictors may interfere.)