similar to: survival::survfit,plot.survfit

For a fitted Cox model, one can either produce the predicted survival curve for a particular "hypothetical" subject (survfit), or the predicted curve for a particular cohort of subjects (survexp). See chapter 10 of Therneau and Grambsch for a long discussion of the differences between these, and the various pitfalls. By default, survfit produces the curve for a hypothetical

Dear all, I am confused with the output of survfit.coxph. Someone said that the survival given by summary(survfit.coxph) is the baseline survival S_0, but some said that is the survival S=S_0^exp{beta*x}. Which one is correct? By the way, if I use "newdata=" in the survfit, does that mean the survival is estimated by the value of covariates in the new data frame? Thank you very much!

Dear all, I have a serious problem to solve my model. I study over exploitation of fish in the bay of biscay (france). I know only the level of catch and the fishing effort (see data below) by year. My model is composed by the following equations: * the growth function Gt(St) = r*St*(1-St/sbar) with Gt the growth of each period t r intrinsec growth of the stock sbar carriyng capacity of the

Dear R-help, I am trying to obtain the baseline survival estimate of a fitted Cox model (S_0 (t)). I know that previous posts have said use 'basehaz' but this gives the baseline hazard function and not the baseline survival estimate. Is there a way to obtain the baseline survival estimate or do I have to use the formula which does something like S(t) = exp[- the integral from 0 to t of

One approach is to use the rms package's cph and Mean.cph functions. Mean.cph (cph calls coxph and can compute Kaplan-Meier and other survival estimates) can compute mean restricted life. Frank Dinesh W wrote > I am using survfit to generate a survival curve. My population is such > that my x axis is in days and i have a starting population of say 10,000 > of which say only 2000 are

Hi, I've attached two files with the sources for a function to implement the finite difference method for solving a particular differential equation. One of them works correctly, the other gives wrong results or returns an error, depending on the version of R. The difference between them is that in the 'broken' version in line 42 I check if the items in the two-dimensional array

Hi, I''ve added a custom library called lib\AccountSystem like so: "module AccountSystem SINGLE = 1 MULTIPLE = 2 class << self attr_accessor :account_system_type end end" Now I wanna configure AccountSystem.account_system_type=AccountSystem::SINGLE in one app. I used an initializer: config/initializers/account_initialization.rb where I put this line in. I

Dear Prof. Brostr?m, Dear R-mailinglist, first of all thanks a lot for your great effort to incorporate time-varying covariates into aftreg. It works like a charm so far and I'll update you with detailled benchmarks as soon as I have them. I have one more questions regarding Accelerated Failure Time models (with aftreg): You mention that left truncation in combination with time-varying

--- included message ---- Thus, my question is: *What common measures exists for ranking/measuring variable importance of participating variables in a CART model? And how can this be computed using R (for example, when using the rpart package)* ---end ---- Consider the following printout from rpart summary(rpart(time ~ age + ph.ecog + pat.karno, data=lung)) Node number 1: 228 observations,

Hi, I'm sure this should be simple but I can't figure it out! I want to get the median survival calculated by the survfit function and use the value rather than just be able to print it. Something like this: library(survival) data(lung) lung.byPS = survfit(Surv (time, status) ~ ph.ecog, data=lung) # lung.byPS Call: survfit(formula = Surv(time, status) ~ ph.ecog, data = lung) 1

--begin inclusion --- I am trying to extract output information from the survfit function in order to generate a matrix of select output for multiple factors. Specifically, I am interested in extracting the number of events (in the output below: 106, 2, 3). The variable names represented in my function (ee) are shown below, but none of those variables correspond to the column of events as shown

Hi, I am using rpart as a part of my masters' project. I am trying to print out the resulting model using plot() function along with text() function. I am having difficulties with labels being cut-off. In text() function, I am using use.n=T option to get the number of people in each nodes but the on the lower and left part of the plot, the numbers get cut off. Thanks! Linus [[alternative

Hi, I tried openssh on my SONY NEWS-OS 4.2.1R which is 4.3BSD based system. I modified a little(*) to compile openssh and the compilation was successful. Ssh worked but sshd didn't work. I checked the output of 'sshd -d'. It says error: open /dev/tty failed - could not set controlling tty: No such device or address when connected from remote host (FreeBSD 5-current) with ssh. And

Dear developpers, I successfully compiled OpenSSH 2.9p1 which I get via CVS with a little modification. Patch is available at http://www.rc.tutrp.tut.ac.jp/~nakaji/install/NEWS/utils/ref/openssh_cvs-news4.diff.gz But one problem remains. In config.h.in, there is a definition about strftime function /* Define if you have the `strftime' function. */ #undef HAVE_STRFTIME but this

I?m trying to set up proportional hazard model that is stratified with respect to covariate 1 and has an interaction between covariate 1 and another variable, covariate 2. Both variables are categorical. In the following, I try to illustrate the two problems that I?ve encountered, using the lung dataset. The first problem is the warning: To me, it seems that there are too many dummies

Hello R helpers: *My first message didn't pass trough filter so here it's again* I would like to obtain probability of an event for one single patient as a function of time (from survfit.coxph) object, as I want to find what is the probability of an event say at 1 month and what is the probability of an event at 80 months and compare. So I tried the following but it fails miserably. I

I am wondering how to estimate the survival curve for a particular case(s) given a coxph model using this example code: #fit a cox proportional hazards model and plot the #predicted survival curve fit <- coxph( Surv(futime,fustat)~resid.ds+strata(rx)+ecog.ps+age,data=ovarian[1:23,]) z <- survfit(fit,newdata=ovarian[24:26,],individual=F) zs <- z$surv zt <-

Hi! I came across R just a few days ago since I was looking for a toolbox for cox-regression. I?ve read "Cox Proportional-Hazards Regression for Survival Data Appendix to An R and S-PLUS Companion to Applied Regression" from John Fox. As described therein plotting survival-functions works well (plot(survfit(model))). But I?d like to do some manipulation with the survival-functions

This is from the current CVS: % make ... In file included from config.h:629, from /home/mo/project/openssh_cvs/includes.h:20, from /home/mo/project/openssh_cvs/scp.c:77: /home/mo/project/openssh_cvs/defines.h:208: warning: redefinition of `clock_t' /usr/include/time.h:60: warning: `clock_t' previously declared here gcc -o scp scp.o -L.

First, here is your message as it appears on R-help. On 10/14/2012 05:00 AM, r-help-request@r-project.org wrote: > I?m trying to set up proportional hazard model that is stratified with > respect to covariate 1 and has an interaction between covariate 1 and > another variable, covariate 2. Both variables are categorical. In the > following, I try to illustrate the two problems that