[R] Partial F-test comparing full and reduced regression models

Peter Dalgaard p.dalgaard at biostat.ku.dk
Sun May 1 21:52:32 CEST 2005

Jim Milks <jrclmilks at joimail.com> writes:

> 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?

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.)

   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907

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