• using R version 2.11.0 Under development (unstable) (2010-01-14 r50981)
• using session charset: UTF-8
• checking for file 'coxphf/DESCRIPTION' ... OK
• checking extension type ... Package
• this is package 'coxphf' version '1.0-2'
• checking package name space information ... OK
• checking package dependencies ... OK
• checking if this is a source package ... OK
• checking for executable files ... OK
• checking whether package 'coxphf' can be installed ... OK
• checking package directory ... OK
• checking for portable file names ... OK
• checking for sufficient/correct file permissions ... OK
• checking DESCRIPTION meta-information ... OK
• checking top-level files ... OK
• checking index information ... OK
• checking package subdirectories ... OK
• checking R files for non-ASCII characters ... OK
• checking R files for syntax errors ... OK
• checking whether the package can be loaded ... OK
• checking whether the package can be loaded with stated dependencies ... OK
• checking whether the package can be unloaded cleanly ... OK
• checking whether the name space can be loaded with stated dependencies ... OK
• checking whether the name space can be unloaded cleanly ... OK
• checking for unstated dependencies in R code ... OK
• checking S3 generic/method consistency ... OK
• checking replacement functions ... OK
• checking foreign function calls ... OK
• checking R code for possible problems ... NOTE
  decomposeSurv: no visible binding for global variable ‘response’
• checking Rd files ... NOTE
  prepare_Rd: coxphfplot.Rd:70-71: Dropping empty section \note
  prepare_Rd: coxphftest.Rd:61-62: Dropping empty section \note
• checking Rd metadata ... OK
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• checking line endings in C/C++/Fortran sources/headers ... OK
• checking line endings in Makefiles ... OK
• checking for portable use of $BLAS_LIBS ... OK
• checking examples ... ERROR
  Running examples in 'coxphf-Ex.R' failed.
  The error most likely occurred in:
  
  > ### * coxphf
  >
  > flush(stderr()); flush(stdout())
  >
  > ### Name: coxphf
  > ### Title: Cox regression with Firth's penalized likelihood
  > ### Aliases: coxphf
  > ### Keywords: survival
  >
  > ### ** Examples
  >
  > # fixed covariate and monotone likelihood
  > time<-c(1,2,3)
  > cens<-c(1,1,1)
  > x<-c(1,1,0)
  > sim<-cbind(time,cens,x)
  > sim<-data.frame(sim)
  > coxphf(sim, formula=Surv(time,cens)~x) #convergence attained!
  coxphf(formula = Surv(time, cens) ~ x, data = sim)
  Model fitted by Penalized ML
  Confidence intervals and p-values by Profile Likelihood
  
  coef se(coef) exp(coef) lower 0.95 upper 0.95 Chisq p
  x 1.329104 1.929072 3.777658 0.2914006 528.7306 0.9151565 0.3387499
  
  Likelihood ratio test=0.9151565 on 1 df, p=0.3387499, n=3
  
  > coxph(sim, formula=Surv(time,cens)~x) #no convergence!
  Warning in fitter(X, Y, strats, offset, init, control, weights = weights, :
  Ran out of iterations and did not converge
  Call:
  coxph(formula = Surv(time, cens) ~ x, data = sim)
  
  
  coef exp(coef) se(coef) z p
  x 21.0 1.29e+09 29282 0.000716 1
  
  Likelihood ratio test=2.2 on 1 df, p=0.138 n= 3
  >
  > # time-dependent covariate
  > test2 <- data.frame(list(start=c(1, 2, 5, 2, 1, 7, 3, 4, 8, 8),
  + stop =c(2, 3, 6, 7, 8, 9, 9, 9,14,17),
  + event=c(1, 1, 1, 1, 1, 1, 1, 0, 0, 0),
  + x =c(1, 0, 0, 1, 0, 1, 1, 1, 0, 0) ))
  >
  > summary( coxphf( formula=Surv(start, stop, event) ~ x, data=test2))
  coxphf(formula = Surv(start, stop, event) ~ x, data = test2)
  
  Model fitted by Penalized ML
  Confidence intervals and p-values by Profile Likelihood
  
  coef se(coef) exp(coef) lower 0.95 upper 0.95 Chisq p
  x -0.1213111 0.7920055 0.8857583 0.2031077 4.21294 0.02621190 0.8713839
  
  Likelihood ratio test=0.02621190 on 1 df, p=0.8713839, n=10
  Wald test = 0.02346091 on 1 df, p = 0.8782646
  
  Covariance-Matrix:
  x
  x 0.6272728
  >
  >
  > # time-dependent effect
  > # the coxphf function can handle interactions of a (fixed or time-dependent)
  > # covariate with time
  > # such that the hazard ratio can be expressed as a function of time
  >
  > summary(coxphf(formula=Surv(start, stop, event)~x+x:log(stop), data=test2, firth=FALSE))
  coxphf(formula = Surv(start, stop, event) ~ x + x:log(stop),
  data = test2, firth = FALSE)
  
  Model fitted by Standard ML
  Confidence intervals and p-values by Profile Likelihood
  
  coef se(coef) exp(coef) lower 0.95 upper 0.95 Chisq p
  x 1.854398 27.038116 6.387854e+00 NaN NaN 0 1
  log(stop) -11.976909 9.618655 6.287737e-06 NaN NaN 0 1
  x:log(stop) -1.548477 13.168942 2.125715e-01 NaN NaN 0 1
  
  Likelihood ratio test=-27.09733 on 3 df, p=1, n=10
  Wald test = 2.551232 on 3 df, p = 0.4661035
  
  Covariance-Matrix:
  x log(stop) x:log(stop)
  x 731.0597 127.75834 -355.4551
  log(stop) 127.7583 92.51852 -61.1405
  x:log(stop) -355.4551 -61.14050 173.4210
  >
  > # note that coxph would treat x:log(stop) as a fixed covariate
  > # (computed before the iteration process)
  > # coxphf treats x:log(stop) as a time-dependent covariate which
  > # changes (for the same individual!) over time
  >
  >
  > # time-dependent effect with monotone likelihood
  >
  > test3 <- data.frame(list(start=c(1, 2, 5, 2, 1, 7, 3, 4, 8, 8),
  + stop =c(2, 3, 6, 7, 8, 9, 9, 9,14,17),
  + event=c(1, 0, 0, 1, 0, 1, 1, 0, 0, 0),
  + x =c(1, 0, 0, 1, 0, 1, 1, 1, 0, 0) ))
  >
  > summary( coxphf( formula=Surv(start, stop, event) ~ x+x:log(stop), data=test3))