frailty and time-dependent covariate

Hello,

I'm trying to estimate a cox model with a frailty variable and 
time-dependent covariate (below there is the statement I use and the 
error message). It's seems to be impossible, because every time I add 
the time-dependent covariate the model doesn't converge. Instead, if I 
estimate the same model without the time-dependent covariate it's 
converge. I'd like knowing if it's a statistical problem due to the 
model formula or if it could be a problem related to my data.
The message you quote probably does not indicate a convergence problem, 
since it is only in "iterations 1 3".

Howver, there does seem to be a bug with interactions of any sort in 
frailty models, something connected with reordering terms.  You could try 
defining a variable by hand for your interaction term and fitting the 
model that way.

Incidentally, I am not nearly as enthusiastic about the frailty models as 
many users seem to be.  For most multivariate survival problems I 
wouldn't want to fit a frailty model, and I'm not sure that I would trust 
the penalised likelihood approximation if I did.   The exception would be 
situations where I was actually interested in the variance components, as 
in Dr Therneau's new "kinship" package for linkage analysis with survival 
data.

 	-thomas
Thanks a lot

Emanuela Rossi

fit_19_1<-coxph(Surv(DATA_INI1,DATA_FIN1,EVENT1)~ 
V1+V2+alt1+alt2+strata(autocorr1)+cap1+SP+SP2+SP3+SP3:log(DATA_FIN1)+D1500+D3000+D4500+frailty.gaussian(ID),data=SURV1)
Warning messages:
1: Inner loop failed to coverge for iterations 1 3 in: coxpenal.fit(X, Y, strats, offset, init = init, control, weights = weights,
2: longer object length
       is not a multiple of shorter object length in: offset + coxfit$fcoef[x[, fcol]]
3: X matrix deemed to be singular; variable 8 in: coxph(Surv(DATA_INI1, DATA_FIN1, EVENT1) ~ V1 + V2 + alt1 + alt2 +

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Thomas Lumley			Assoc. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle

frailty and time-dependent covariate

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