Thanks to Brian's suggestion of using the logLik() function, I've dug a
little deeper. I definitely think f1 and f2 are nested models. For example,
by adding x2 to fmla1, we obtain a formula that quite clearly nests fmla1
and achieves the same log likelihood as that obtained for f2. Here is the
extra code to show this:

fmla3 = y~I(x1+x2)+x2
f3=glm(fmla3)
logLik(f1); logLik(f2); logLik(f3)

If f2=f3, as the log likelihoods would suggest, then this gives us a
workaround: define the intermediate formula fmla3 and the fit f3 as above,
and then conduct the analysis of variance between models f1 and f3 instead
of f1 and f2. This doesn't offend anova.rq() any longer:

f3.qr = rq(fmla3)
anova(f1.qr,f3.qr) #this is actually anova(f1.qr, f2.qr) which resulted in
an error earlier

-Galen

On Fri, Apr 20, 2012 at 6:47 PM, Brian S Cade <cadeb@usgs.gov> wrote:

> Galen:  Interesting, first time I tried it I couldn't get anova.glm to
> compute the p-values (got a warning) but I tried it again and it worked.
> Your larger (alternative hypothesis) model is  y = B0 + B1*x1 + B2*x2 + e
> and your smaller (null hypotheisis) model is y = B0 + B3*(x1 + x2).  So  I
> guess I see that what you're trying to test in this case is that B1 = B2.
>  I don't think Roger Koenker anticipated such a test with anova.rq.  Other
> options besides using information criteria (AIC, BIC, etc) for comparing
> nonnested models include the Vuong test.  But not sure how readily the
> theory of Vuong's test (like a paired t-test) extends to quantile
> regression.
>
> Brian
>
> Brian S. Cade, PhD
>
> U. S. Geological Survey
> Fort Collins Science Center
> 2150 Centre Ave., Bldg. C
> Fort Collins, CO  80526-8818
>
> email:  brian_cade@usgs.gov
> tel:  970 226-9326
>
>
>  From: Galen Sher <galensher@gmail.com> To: Brian S Cade <cadeb@usgs.gov>
> Date: 04/20/2012 09:59 AM Subject: Re: [R] ANOVA in quantreg - faulty
> test for 'nesting'?
> ------------------------------
>
>
>
> Thanks Brian. I think anova.glm() requires the user to specify the
> appropriate distribution. In the example above, if I use either of the
> following commands
>
> anova(f1,f2,test="Chisq") #or
> anova(f1,f2,test="F")
>
> then anova.glm() will compute and display p-values associated with the
> deviance statistics. The reason I thought these models are nested is
> because the first model can be thought of as the second model estimated
> under an additional linear equality constraint. I suppose that's less of an
> R question and more of a regression question.
>
> Thanks for the logLik suggestion. In the absence of more information I'll
> have to do that - I'm just wary of conducting the test myself!
>
> Regards,
> Galen
>
> On Fri, Apr 20, 2012 at 4:31 PM, Brian S Cade <*cadeb@usgs.gov*<cadeb@usgs.gov>>
> wrote:
> Galen:  Actually don't see how the models are nested (ask yourself what
> parameter in the model with 3 parameters is set to zero in the 2 parameter
> model?) and indeed if I try your code anova.glm will compute the difference
> in deviance between the two models but it does not compute a probability
> value for that difference in deviance as that would not make sense for
> models that aren't nested.   Koenker's implementation of anova.rq
> immediately detects that the models aren't nested so doesn't even compute
> the deviance difference.  You could use the logLik function on the rq
> objects to get their log likelihoods or use AIC (BIC) to compare the
> quantile regression models.
>
> Brian
>
> Brian S. Cade, PhD
>
> U. S. Geological Survey
> Fort Collins Science Center
> 2150 Centre Ave., Bldg. C
> Fort Collins, CO  80526-8818
>
> email:  *brian_cade@usgs.gov* <brian_cade@usgs.gov>
> tel:  *970 226-9326* <970%20226-9326>
>
>   From: galen <*galensher@gmail.com* <galensher@gmail.com>>  To: *
> r-help@r-project.org* <r-help@r-project.org>  Date: 04/19/2012 02:40 PM
> Subject: [R] ANOVA in quantreg - faulty test for 'nesting'?  Sent by: *
> r-help-bounces@r-project.org* <r-help-bounces@r-project.org>
>
>  ------------------------------
>
>
>
>
> I am trying to implement an ANOVA on a pair of quantile regression models
> in
> R. The anova.rq() function performs a basic check to see whether the models
> are nested, but I think this check is failing in my case. I think my models
> are nested despite the anova.rqlist() function saying otherwise. Here is an
> example where the GLM ANOVA regards the models as nested, but the quantile
> regression ANOVA tells me the models aren't nested:
>
> y = rnorm(100)
> x1 = rnorm(100)
> x2 = rnorm(100)
>
> fmla1 = y~I(x1+x2)
> fmla2 = y~x1+x2
>
> f1 = glm(fmla1)
> f2 = glm(fmla2)
>
> anova(f1,f2) #This works
>
> f1.qr = rq(fmla1)
> f2.qr = rq(fmla2)
>
> anova(f1.qr,f2.qr) #Error!
> #Error in anova.rqlist(object, ...) : Models aren't nested
>
> Are the models in fact not nested? If they are nested, is there an easy
> workaround I could use? Many thanks in anticipation.
>
> --
> View this message in context: *
> http://r.789695.n4.nabble.com/ANOVA-in-quantreg-faulty-test-for-nesting-tp4571994p4571994.html
> *<http://r.789695.n4.nabble.com/ANOVA-in-quantreg-faulty-test-for-nesting-tp4571994p4571994.html>
> Sent from the R help mailing list archive at Nabble.com.
>
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