Re: [R] Doing partial-f test for stepwise regression

From: Frank E Harrell Jr <f.harrell_at_vanderbilt.edu>
Date: Sun 01 Apr 2007 - 14:23:18 GMT

Petr Klasterecky wrote:

> And what about to read the help page ?anova ...?
> 
>  >>>
> When given a sequence of objects, 'anova' tests the models against
>       one another in the order specified.
> <<<
> 
> Generally you almost never fit a full model (including all possible 
> interactions etc) - no one can interpret such complicated models. Anova 
> gives you a comparison between a broader model (the first argument to 
> anova) and its submodel(s).

True you might not fit a model with high-order interactions, but the full pre-specified model is the only one whose standard errors and test statistics work as advertised.

Frank

> 
> Petr
> 
> zhuanyi@zay.name napsal(a):

>> Hello all,
>> I am trying to figure out an optimal linear model by using stepwise
>> regression which requires partial f-test, I did some Googling on the
>> Internet and realised that someone seemed to ask the question before:
>>
>> Jim Milks <jrclmilks@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.)
>> However, in the answer provided by Mr. Peter Dalgaard,(use
>> anova(model1,model2) I could not understand what model1 and model2 are
>> supposed to referring to, which one is supposedly to be the full model and
>> which one is to be the partial model? Or it does not matter?
>>
>> Thanks in advance for help from anyone!
>>
>> Regards,
>> Anyi Zhu
>>
>> ______________________________________________
>> R-help@stat.math.ethz.ch mailing list
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University

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Received on Mon Apr 02 04:57:16 2007

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