[R] inconsistency between anova() and summary() of glmmPQL

[Liaw, Andy]

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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