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I'm doing survival analysis with interval-cesored data and I'm using intcox() function from the intcox package in R, which is based on the coxph function.

The function returns the output without likelihood ratio test values:

> intcox(surv~sexo,data=dados)
Call:
intcox(formula = surv ~ sexo, data = dados)

             coef exp(coef) se(coef)  z  p
sexojuvenil  2.596      13.4       NA NA NA
sexomacho   -0.105       0.9       NA NA NA

Likelihood ratio test=NA  on 2 df, p=NA  n= 156

I don't know why this is happening... Here is the application of the coxph() function to the same data:

> coxph(Surv(dias_seg,status)~sexo,data=dados)
Call:
coxph(formula = Surv(dias_seg, status) ~ sexo, data = dados)

              coef exp(coef) se(coef)      z       p
sexojuvenil  2.320    10.172    0.630  3.684 0.00023
sexomacho   -0.169     0.844    0.252 -0.671 0.50000

Likelihood ratio test=9.28  on 2 df, p=0.00967  n= 156, number of events= 77 


str(dados$sexo)
 Factor w/ 3 levels "femea","juvenil",..: 3 3 3 3 3 3 3 3 3 3 ...

Can you help me to solve this problem?
Thanks in advance.

JMarcelino
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1 Answers1

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I was told by Volkmar Henschel (author of intcox package) that the "The fit with intcox gives an object of class ”coxph” without the standard errors of the regression coefficients".

More descriptions on this document: ftp://ftp.auckland.ac.nz/pub/software/CRAN/doc/vignettes/intcox/intcox.pdf

JMarcelino
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    Another useful reference on interval censored survival analysis in R. "Tutorial on methods for interval-censored data and their implementation in R. Statistical Modelling 2009; 9(4): 259–297". In section 4.2 it specifically discusses the intcox() function and the Cox model fitted via the ICM method. – Chris Feb 11 '14 at 04:40