Dear Elisabetta,
I have no direct answer to your question, but a suggestion: Use the
'coxme' function (in the package with the same name). In the help page
for 'frailty' (survival) you will find: "The coxme package has
superseded this method. It is faster, more stable, and more flexible."
Hth, Göran
On 2016-09-05 11:42, Elisabetta Petracci wrote:
Dear users,
I am fitting a conditional gap time frailty cox model weighting
observations by means of inverse probability time dependent weigths.
Attached find the self-explaining dataset.
I have used the following sintax:
coxph(Surv(gaptstart,gaptstop,status)~treat+strata(nrecord01)+frailty(id,distribution="gamma",method="em"),
data=dataNOTDrr,weights=dataNOTDrr$weight)
And I get the following warning:
Warning message:
In coxpenal.fit(X, Y, strats, offset, init = init, control, weights =
weights, :
Inner loop failed to coverge for iterations 3 4
I have tried to:
- leave out the weights but I get the error anyway
- to randomly select a subset of patients and I don't get the error. This
seems to suggest that the problem is with some observations.
Any suggestion?
Many thanks,
Elisabetta
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