R help - Mar 2006 - inconsistency between anova() and summary() of glmmPQL

Dear All,

Could anyone explain me how it is possible that one factor 
in a glmmPQL model is non-significant according to the 
anova() function, whereas it turns out to be significant 
(or at least some of its levels differ significantly from 
some other levels) according to the summary() function. 
What is the truth, which results shall I believe? And, is 
there any other way of testing for the overall effect of a 
factor in glmmPQL, than anova()?

Thanks for help,
Istvan

To quote one of my professors, it usually doesn't make sense to ask
questions like `Is variable X significant?'  (Or, sort of more formally,
testing H0: beta_j = 0 vs. H1: beta_j != 0.)  If `X' is the _only_ variable
you will ever consider, then the question can make sense.  Otherwise, you
need more context: what other variables are you putting into the model?

The `inconsistency' you saw is because of difference in context.  The test
you see in summary() adds terms in the model sequentially, so provides tests
of a sequence of nested models.  OTHO, each row in the output of anova() is
comparing two models: the model with all terms (`full model') vs. the one
with all terms except the term being considered (`reduced model').  Which
one is `right' depends on which hypothesis matches your research question.

HTH,
Andy

From: I.Szentirmai
> 
> Dear All,
> 
> Could anyone explain me how it is possible that one factor 
> in a glmmPQL model is non-significant according to the 
> anova() function, whereas it turns out to be significant 
> (or at least some of its levels differ significantly from 
> some other levels) according to the summary() function. 
> What is the truth, which results shall I believe? And, is 
> there any other way of testing for the overall effect of a 
> factor in glmmPQL, than anova()?
> 
> Thanks for help,
> Istvan
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide! 
> http://www.R-project.org/posting-guide.html
> 
>

My apologies:  I got the descriptions of tests in summary() and anova()
backward.

Cheers,
Andy

From: I.Szentirmai
> 
> Dear Andy,
> 
> Thanks a lot for clarifying this for me.
> 
> However, to me it seems that anova is the one that 
> provides the results of a sequential test since whether a 
> factor is significant depends on its position among all 
> factors in the model. I ran my model including f1, f2 and 
> f3 with different orders of these factors (model 1: 
> y=f1+f2+f3; model 2: y=f3+f2+f1), and I got really 
> different results. The results in the summary output 
> however, did not depend on the order of the factors.
> 
> Maybe I didn't get you right, but this seems to be in 
> contrast with what you wrote me.
> 
> Thanks,
> Istvan
> 
> 
> On Wed, 1 Mar 2006 11:53:16 -0500
>   "Liaw, Andy" <andy_liaw at merck.com> wrote:
> > To quote one of my professors, it usually doesn't make 
> >sense to ask
> > questions like `Is variable X significant?'  (Or, sort 
> >of more formally,
> > testing H0: beta_j = 0 vs. H1: beta_j != 0.)  If `X' is 
> >the _only_ variable
> > you will ever consider, then the question can make 
> >sense.  Otherwise, you
> > need more context: what other variables are you putting 
> >into the model?
> > 
> > The `inconsistency' you saw is because of difference in 
> >context.  The test
> > you see in summary() adds terms in the model 
> >sequentially, so provides tests
> > of a sequence of nested models.  OTHO, each row in the 
> >output of anova() is
> > comparing two models: the model with all terms (`full 
> >model') vs. the one
> > with all terms except the term being considered 
> >(`reduced model').  Which
> > one is `right' depends on which hypothesis matches your 
> >research question.
> > 
> > HTH,
> > Andy
> > 
> >From: I.Szentirmai
> >> 
> >> Dear All,
> >> 
> >> Could anyone explain me how it is possible that one 
> >>factor 
> >> in a glmmPQL model is non-significant according to the 
> >> anova() function, whereas it turns out to be significant 
> >> (or at least some of its levels differ significantly 
> >>from 
> >> some other levels) according to the summary() function. 
> >> What is the truth, which results shall I believe? And, 
> >>is 
> >> there any other way of testing for the overall effect of 
> >>a 
> >> factor in glmmPQL, than anova()?
> >> 
> >> Thanks for help,
> >> Istvan
> >> 
> >> ______________________________________________
> >> R-help at stat.math.ethz.ch mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide! 
> >> http://www.R-project.org/posting-guide.html
> >> 
> >> 
> > 
> > 
> > 
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