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Cox with frailty

To: s-news@lists.biostat.wustl.edu
Subject: Cox with frailty
From: Mr J Gomez <ecsfi@csv.warwick.ac.uk>
Date: Thu, 21 Jun 2001 19:32:37 +0100
Organization: University of Warwick
Dear all

I am estimating a Cox model with frailty. I am running Splus 2000 under
Windows 98 in a Pentium III (128 MB RAM). When I run the model, the
program says that the "inner loop failed to converge". Can you help me
with this? Is that a problem?

Thanks

Jaime Gomez.

The results of running the model follow:

Call:
coxph(formula = Surv(ANOI, ANOF, CENSURA) ~ log(SIZE) + INTER + PROFI +
PROXIC + PROXIE + DENSI + MGROW + DEPHA + OBJEH + NUMSB + CMOBC +
 NMARK + (NMARK^2) + frailty(NCAJA), data = AVER, na.action = na.omit,
eps = 0.0001, iter.max = 100, method = "efron")

                     coef se(coef)      se2  Chisq   DF        p
     log(SIZE)   1.337246 0.161832 0.146554  68.28  1.0 2.2e-016
         INTER   2.224514 1.706520 1.585002   1.70  1.0 1.9e-001
         PROFI   0.374407 0.212975 0.197735   3.09  1.0 7.9e-002
        PROXIC   2.524886 0.201795 0.200045 156.55  1.0 0.0e+000
        PROXIE   1.739035 0.233397 0.232317  55.52  1.0 9.3e-014
         DENSI  -0.000201 0.000607 0.000606   0.11  1.0 7.4e-001
         MGROW   0.003407 0.025043 0.024962   0.02  1.0 8.9e-001
         DEPHA   0.084440 0.495170 0.491879   0.03  1.0 8.6e-001
         OBJEH  -2.960687 1.825344 1.819987   2.63  1.0 1.0e-001
         NUMSB  -0.100384 0.026414 0.026341  14.44  1.0 1.4e-004
         CMOBC -12.766192 3.991228 3.162052  10.23  1.0 1.4e-003
         NMARK   0.014706 0.047282 0.043106   0.10  1.0 7.6e-001
    I(NMARK^2)  -0.000160 0.000830 0.000770   0.04  1.0 8.5e-001
frailty(NCAJA)                               63.44 24.6 2.8e-005

Iterations: 6 outer, 411 Newton-Raphson
     Variance of random effect= 0.571   EM likelihood = -1053.1
Degrees of freedom for terms=  0.8  0.9  0.9  1.0  1.0  1.0  1.0  1.0
1.0  1.0  0.6  0.8  0.9 24.6
Likelihood ratio test=952  on 36.36 df, p=0  n= 34529
Warning messages:
  Inner loop failed to coverge for iterations 1 2 3 4 in:
coxpenal.fit(X, Y, strats, offset, init = init, iter.max = iter.max,
outer.max =
outer.max, eps = eps, toler.chol = toler.chol, weights =   ...



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