On Wed, Jul 20, 2011 at 5:42 AM, AO_Statistics <abouesl...@gmail.com> wrote: > > Terry Therneau-2 wrote: >> >> This query of "why do SAS and S give different answers for Cox models" >> comes >> up every so often. The two most common reasons are that >> a. they are using different options for the ties >> b. the SAS and S data sets are slightly different. >> You have both errors. >> >> First, make sure I have the same data set by reading a common file, and >> then >> compare the results. >> >> tmt54% more sdata.txt >> 1 0.0 0.5 0 0 >> 1 0.5 3.0 1 1 >> 2 0.0 1.0 0 0 >> 2 1.0 1.5 1 1 >> 3 0.0 6.0 0 0 >> 4 0.0 8.0 0 1 >> 5 0.0 1.0 0 0 >> 5 1.0 8.0 1 0 >> 6 0.0 21.0 0 1 >> 7 0.0 3.0 0 0 >> 7 3.0 11.0 1 1 >> >> tmt55% more test.sas >> options linesize=80; >> >> data trythis; >> infile 'sdata.txt'; >> input id start end delir outcome; >> >> proc phreg data=trythis; >> model (start, end)*outcome(0)=delir/ ties=discrete; >> >> proc phreg data=trythis; >> model (start, end)*outcome(0)=delir/ ties=efron; >> >> >> tmt56% more test.r >> trythis <- read.table('sdata.txt', >> col.names=c("id", "start", "end", "delir", >> "outcome")) >> >> coxph(Surv(start, end, outcome) ~ delir, data=trythis, ties='exact') >> coxph(Surv(start, end, outcome) ~ delir, data=trythis, ties='efron') >> >> ----------------- >> I now get comparable answers. Note that Cox's "exact partial likelihood" >> is >> the correct form to use for discrete time data. I labeled this as the >> 'exact' >> method and SAS as the 'discrete' method. The "exact marginal likelihood" >> of >> Prentice et al, which SAS calls the 'exact' method is not implemented in >> S. >> >> As to which package is more reliable, I can only point to a set of >> formal test >> cases that are found in Appendix E of the book by Therneau and Grambsch. >> >> [...] >> >> > > > I am processing estimations of regression parameters in the Cox model for > recurrent event data with time-dependent covariates. As my data sets contain > a lot of ties, I use the "discrete" method of SAS ("PHREG" procedure) and > "exact" option in R ("coxph" function of "survival" package). > > Despite the high computation time (up to 45s), I always get estimations > without error or warning message with the "PHREG" procedure. > On the other hand, when I use R software (latest version 2.13.11 on 32 or 64 > bits), I sometimes get different estimates from those obtained with SAS and > I get various warnings. And some other time I don't get any result, R > freezes and does not respond. > > In order to understand, I have tried some tests from your examples. It turns > out that dysfunctions appear when the proportion of ties become important : > Edited down to results: R > coef exp(coef) se(coef) z p > delir 22.5 6.06e+09 15460 0.00146 1 SAS > estimate delir : 20.52466 > se : 5689 R > > coef exp(coef) se(coef) z p > delir -20.8 9.42e-10 42054 -0.000494 1 SAS > estimate delir : -17.78257 > se : 9383 > Pr > Khi 2 : 0.9985 > convergence status : "Convergence criterion (GCONV=1E-8) satisfied."
The warning and error messages are correct here. Look at the point estimate. It's a log hazard ratio of about 20 in one case and about -20 in the other case. The true partial maximum likelihood estimator is infinite. The estimated standard errors are meaningless, since the partial likelihood isn't close to quadratic at the maximum. -thomas -- Thomas Lumley Professor of Biostatistics University of Auckland ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.