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Re: st: GLMs that fail - an effect (Hauck-Donner)
Allan was reporting on estimation problems when the success/failure
was predicted perfectly, in Stata jargon. One solution out of this
problem would be to switch to the Bayesian world and put some priors
on your estimates (because otherwise you are estimating the
probability to be 1, and the variance of the binomial with p=1 is
p(1-p)=0, and so the information matrix is singular, and what not).
That way, you can get some spread of the posterior. I am not sure if
this is an option for clinical trials -- all I know is that it is a
heavily regulated area... And I am not sure what do you mean by robust
procedures here; you can specify -robust- option with -logit-, but it
would not resolve the generic issue of lack of information (zero
variance). Those are just my two cents here.
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