françoise Hennequin
2002-Jan-10 17:58 UTC
[R] question about survival datas with repeated mesurements
I have to study censured datas concernig the occurence of infection at the point of insertion of catheter in patients with renal disease. Catheter may be removed for ather reasons than infection, in this case, the observation is censored. Each has exactly 2 observations. The question are the pronostic factors of infection (the other variables are; age, sex, type of renal disease...). Could you indicate me what is the R function to use in case of repeated consored datas? Than you very much.. -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-help/attachments/20020110/b23785d9/attachment.html
Thomas Lumley
2002-Jan-10 19:22 UTC
[R] question about survival datas with repeated mesurements
On Thu, 10 Jan 2002, [iso-8859-1] françoise Hennequin wrote:> I have to study censured datas concernig the occurence of infection at > the point of insertion of catheter in patients with renal disease. > Catheter may be removed for ather reasons than infection, in this case, > the observation is censored. Each has exactly 2 observations. The > question are the pronostic factors of infection (the other variables > are; age, sex, type of renal disease...). Could you indicate me what is > the R function to use in case of repeated consored datas? Than you very > much..I assume that you are interested in the relationships between time to infection and the prognostic factors (rather than being interested primarily in the amount of correlation within a person, for example) The cluster() feature in coxph() is designed for this sort of data. If you have two records per person with eg id time status age 1 50 1 66 1 40 0 66 2 80 0 75 2 70 1 75 ... then you can do coxph(Surv(time,status)~age+cluster(id)) to model the marginal rates of infection. That much is easy. The tricky part is that there are several ways to code the times. If you have two catheters being infected at, say, 50 and 70 days from the start of the study you could code the two times as 50 and 70, or 50 and 20. You could also code two time intervals [0,50] and [50,70] by specifying an entry time for each record id time status 1 50 1 1 70 1 id time status 1 50 1 1 20 1 id entry exit status 1 0 50 1 1 50 70 1 (in this case you would use Surv(entry,exit,status) in the model formula. If you aren't sure about this then one place to look is a nice review paper by Therneau & Hamilton in "Statistics in Medicine" 16: 2029--2047 (and some other useful papers in that issue of the journal). -thomas Thomas Lumley Asst. Professor, Biostatistics tlumley at u.washington.edu University of Washington, Seattle -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Jim Lindsey
2002-Jan-11 12:49 UTC
[R] question about survival datas with repeated mesurements
> I have to study censured datas concernig the occurence of infection at > the point of insertion of catheter in patients with renal disease. > Catheter may be removed for ather reasons than infection, in this case, > the observation is censored. Each has exactly 2 observations. The > question are the pronostic factors of infection (the other variables > are; age, sex, type of renal disease...). Could you indicate me what is > the R function to use in case of repeated consored datas? Than you very > much..=20Virtually all of the functions in my repeated library handle censored data. at www.luc.ac.be/~jlindsey/rcode.html Jim -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._