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Re: coxph problem (Cannot coerce mode list to integer: list(eps =...)

To: <s-news@wubios.wustl.edu>
Subject: Re: coxph problem (Cannot coerce mode list to integer: list(eps =...)
From: "Latha Raja" <lraja@i-com.com>
Date: Tue, 9 Dec 2003 23:38:05 -0500
Thread-index: AcO+bnju8qOuEF44Qae48TtajzsmYQAZxxxg
Thread-topic: coxph problem (ran out of iteration...)
HI,
It is me again!  I try to fix below problem by adding the following term into 
coxph function and now I am getting the following message!  Can anybody help me 
solve this problem?

Thank you ind advance for your help!

Regards,

Latha

Message I am getting now is 

"Cannot coerce mode list to integer: list(eps = 1e-006, toler.chol = 
1.81898940354586e-012, iter.max = 15, toler.inf = 0.001, outer.max = 10,....."

the code I was running:
methd1 <- function(n, b, t)
{
        x <- runif(n, 0, 1)
        y <- 1 - exp( - t)^exp(b * x)
        c <- runif(n, 0, 0.5)
        ttt <- ifelse(y <= c, y, c)
        delt <- ifelse(y <= c, 1, 0)
        datmethod1 <- data.frame(x, ttt, delt)
        ss <- Surv(ttt, delt)
        cox.fun <- coxph(Surv(ttt, delt) ~ x, datmethod1, weights = 1, 
coxph.control(eps = 1e-006, iter.max
                 = 15))
        cox.fun
}



>  -----Original Message-----
> From:         Latha Raja  
> Sent: December 9, 2003 8:07 AM
> To:   's-news@wubios.wustl.edu'
> Subject:      coxph problem (ran out of iteration...)
> 
> Hi there,
> I was wondering whether you will be able to help me find the solution to the 
> following problem I am facing. 
> I am getting the following warning message when I was using the coxph in 
> SPLUS and I am not sure why and where it is happening.  I have also printed 
> my code so you can see what I did to receive this warning.
> 
> I would really appreciate if any of you can find out the solution for me:-) 
> 
> Regards,
> Latha
> 
> 
> 
> Warning messages:
>     Ran out of iterations and did not converge in: 
>       fitter(X, Y, strats, offset, init, control,
>       weights ....
> > 
> 
> 
> Code I used:
> > n<-30
> > b<-2  #Cox regression parameter
> > t<-0.106        #Value of t at which the function S(.) is studied
> > x<-runif(n,0,1)  # covariate value
> > y<-1-exp(-t)^exp(b*x)  #Survival time created from 1-(1-F(t))^exp(b*x)
> > c<-runif(n,0,0.5)
> > for (i in 1:n) ttt[i]<- min(y[i],c[i])
> > for (j in 1:n) if (y[j]<=c[j]) delt[j]=1 else delt[j]=0
> > data30106<-data.frame(x=x,ttt=ttt,delt=delt)
> > data30106
>              x        ttt                delt 
>  1 0.488711202 0.13562690    0
>  2 0.855828642 0.33931078    0
>  3 0.931598405 0.20061720    0
>  4 0.292845422 0.17337203    1
>  5 0.958126171 0.09910074    0
>  6 0.044562074 0.06945480    0
>  7 0.201170894 0.14658059    1
>  8 0.165116648 0.12390505    0
>  9 0.231906470 0.15511377    1
> 10 0.013588991 0.06923096    0
> 11 0.447032066 0.22831198    1
> 12 0.059958322 0.11264017    1
> 13 0.007346802 0.10198546    1
> 14 0.479377087 0.23039922    0
> 15 0.156308175 0.03428859    0
> 16 0.794690335 0.33846672    0
> 17 0.738001760 0.29515082    0
> 18 0.381364945 0.20329983    1
> 19 0.591780599 0.01012725    0
>              x        ttt delt 
> 20 0.765888012 0.38724433    0
> 21 0.445477461 0.12077320    0
> 22 0.028177253 0.02744334    0
> 23 0.908368614 0.07864741    0
> 24 0.647047109 0.23249965    0
> 25 0.142004033 0.05859883    0
> 26 0.452978511 0.09875219    0
> 27 0.342493692 0.18964039    1
> 28 0.444275566 0.22721162    1
> 29 0.971535333 0.14329526    0
> 30 0.519449620 0.05668219    0
> > Surv(ttt,delt)
>  [1] 0.13562690+ 0.33931078+ 0.20061720+ 0.17337203 
>  [5] 0.09910074+ 0.06945480+ 0.14658059  0.12390505+
>  [9] 0.15511377  0.06923096+ 0.22831198  0.11264017 
> [13] 0.10198546  0.23039922+ 0.03428859+ 0.33846672+
> [17] 0.29515082+ 0.20329983  0.01012725+ 0.38724433+
> [21] 0.12077320+ 0.02744334+ 0.07864741+ 0.23249965+
> [25] 0.05859883+ 0.09875219+ 0.18964039  0.22721162 
> [29] 0.14329526+ 0.05668219+
> > coxph(Surv(ttt,delt)~x)
> Call:
> coxph(formula = Surv(ttt, delt) ~ x)
> 
> 
>   coef exp(coef) se(coef)      z    p 
> x -355  6.1e-155      805 -0.441 0.66
> 
> Likelihood ratio test=43.9  on 1 df, p=3.53e-011  n=
>  30 
> Warning messages:
>     Ran out of iterations and did not converge in: 
>       fitter(X, Y, strats, offset, init, control,
>       weights ....
> > 
> 

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