st: [Non Stata] Testing nested models with clustering

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

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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