Re: st: [Non Stata] Testing nested models with clustering

[Antoine Terracol <Antoine.Terracol@univ-paris1.fr>]

Thanks Stas.

My problem was that, since my extra parameter is constrained in (0,1) 
(it is the inverse logistic of a parameter in |R), the lower CI limit is 
always larger than zero.

-streg- with frailty has a similar feature because the variance of the 
frailty is constrained to be strictly positive via an exponential 
transformation. The command does not do any test of the null that there 
is no heterogeneity (variance=0) whith clustered std. errs., but does a 
LRT without; hence my "fear" that there was no simple way to test such 
hypotheses with clustered std. errs.

Antoine

Stas Kolenikov wrote:
> You can do a one-sided Wald test with the clustered standard errors
> just fine. The LRT is indeed a disaster, and if you have clustering
> you would probably have a pseudo-likelihood rather than true
> likelihood, anyway (although I am not really familiar with frailty
> models sufficiently well). This means that the distribution of the LRT
> even without a boundary is not a chi-square but a sum of weighted
> chi-squares, Satterthwaite-style. If you truncate this to the
> boundary, all the hell breaks lose. The Wald test however is quite
> simple, clustered standard errors, jackknife standard errors, or
> whatever standard errors you trust in your situation. If the left
> confidence limit covers zero, you don't reject, and can claim there is
> no heterogeneity. I suspect there is one, anyways... otherwise you
> won't be doing the more complicated analysis, right? :))
>
> On 6/16/09, Antoine Terracol <Antoine.Terracol@univ-paris1.fr> wrote:
> > Dear _all,
> >
> >  I have estimated two models using -ml-. The two models are nested, and
> > model B is equivalent to model A if some parameter delta is equal to zero.
> >
> >  I have clustered standard errors, and thus cannot use a LR test to test B
> > against A. Moreover, delta is constrained in (0,1) through a logistic
> > transformation.
> >
> >  In -heckman- with -cluster()-, the corresponding test is a Wald test of
> > atanh(rho)=0; but in -streg, frailty()- with -cluster()-, no test is
> > performed for the null that there is no heterogeneity (without clustering, a
> > LR test for theta=0 is performed).
> >
> >  Should I infer  that there is no proper (and simple) way to test for nested
> > models with clustering when the additional parameter is constrained, and the
> > null is on the boundary?
> >
> >  Best,
> >
> >  Antoine
> >
> >  --
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