similar to: coxph diagnostics plot for shape of hazard function?

Dear All, I am trying to apply the function 'cox.zph' of the library survival, but I receive this error message: not found the object 'residuals.coxph'. I have re-installed the library 'survival' without any change and also a search with RSiteSearch was unsuccessful.. Any suggestion? TIA Giovanni PS: R 2.2.0 Windows XP HE dr. Giovanni Parrinello Section of Medical

-- begin included message --- I am hoping for some advice regarding obtaining the values for the hazard function in a cox regression that I have undertaken. I have a model in the following form, analysed with the package survival (v. 2.34-1) and a log-log plot obtained using Design (v. 2.1-2). For two variables, the lines in the survival curves crossed. The statistician I been obtaining

Dear list: I am attempting to use what I thought would be a pretty straightforward practical application of Cox regression. I figure users of the survival package must have come across this problem before, so I would like to ask you how you dealt with it. I have set up an illustrative example and included it at the end of this post. I took a sample of 100 data points from each of two populations

Dear all, I use the Andersen plot to check for proportional hazards assumption for a factor (say x) in the Cox regression model and obtained a straight line that pass through the origin. However, the formal test done by the R-function cox.zph, which is based on the plot of Schonefeld residuals against time, indicates that proportional hazards assumption is violated. Further, a plot of the score

Hi, I''ve used old ZPH patch under squid 2.4 Stable4 and it works great ! Now I want to patch squid 2.4 stable 5, with new patch, on http://www.it-academy.bg/zph/ I''ve patched and installed squid 2.5 stable 5 succefully, but I can''t get ZPH works. I''m trying with ... $TC class add dev $LANDEV parent 1: classid 1:7 htb rate 1Mbit $TC filter add dev $LANDEV

Hi, I wrote a function that worked well in R, but not in S-Plus, can anyone suggest a solution? > f.coxph.zph<-function(x) { cox.fit <- coxph(Surv(time.cox, status.cox) ~ x, na.action = na.exclude, method = "breslow") fit.zph<-cox.zph(cox.fit,transform='log') fit.zph$table[,3] } yyy is my data frame that contains survial time, censor status and predictor

Dear all, I have a question concerning the p-value. When running coxph I get a p-value = 0. :confused: Can this be true? Why aren?t there decimal points? Is there a way to find out the exact p-value? Here is the output: ---------------------------------------------------------------------------------------------------- Call: coxph(formula = Surv(start, stop, status) ~ Albumin_gproL, data = dial,

Hello, I got error message when applying the plot function to the cox.zph object to create the Schoenfeld residual plots. > plot(zph.revasFit[1]) Error in plot.window(xlim, ylim, log, asp, ...) : need finite 'ylim' values In addition: Warning messages: 1: NaNs produced in: sqrt(x$var[i, i] * seval) 2: no non-missing arguments to min; returning Inf in: min(x) 3: no

To enhance my understanding, and that of my students, I have a question about cox.zph in the survival package. If I have correctly gleaned the high-level point from the 1994 Biometrika paper of Grambsch and Therneau, it looks to me like cox.zph provides a mechanism to test for a simple trend in plots of a function of time, g(t) versus the scaled schoenfeld residuals and it also provides some

You report an error message: > plot(zph.revasFit[1]) Error in plot.window(xlim, ylim, log, asp, ...) : need finite 'ylim' values I have never seen this error before, and I cannot guess what causes it. You need to provide more information, and likely a small data set that produces the problem. Perhaps you have an x variable that is a constant? Terry Therneau

Hi all, I was trying to test the assumption of proportional hazards assumption, I used the cox.zph function >cox.zph(coxfit6) Results are: rho chisq p x1 -0.0396 1.397 2.37e-01 x2 0.1107 9.715 1.83e-03 x3 -0.0885 7.743 5.39e-03 x4 0.0366 1.092 2.96e-01 x5 0.0242 0.455 5.00e-01 GLOBAL

> ... interactions between covariables and time. A model such as "coxph(Surv(ptime, pstat) ~ age + age*ptime, ...." is invalid -- it is not at all what you think. If cph flags this as an error that is a good thing: I should probably add the same message to coxph. > Is is somewhat sensible to use cox.zph() to investigate which variables need time interaction... The cox.zph

Hi, I used to patch my squid with ZPH patch on http://www.it-academy.bg/zph/ > The idea behind this patch is to allow classification > of packets generated from the squid cache engine towards > clients. > The classification is based on whether the content is > being served from cache (a cache HIT), or > is being retrieved from a remote server (a cache MISS). Very useful

Dear List: I have a data frame prepared in the couting process style for including a binary time-dependent covariate. The first few rows look like this. PtNo Start End Status Imp 1 1 0 608.0 0 0 2 2 0 513.0 0 0 3 2 513 887.0 0 1 4 3 0 57.0 0 0 5 3 57 604.0 0 1 6 4 0 150.0 1 0 The outcome

I am using a syntax like coxph(Surv(start, stop, event) ~ X, data) to estimate the effect of X, which may change at each measurement (every 6 months). Is there anyone who knows a way to test the proportional hazard assumption in that case? Thank you in advance Jean-François Boudreau Sherbrooke University [[alternative HTML version deleted]]

Hi all! I have two survival data sets looking at similar effects in different settings. One data set is only right censored, but the other is interval censored. In the right censored data set, there is an effect of one factor that causes very different shapes in survival curves (and non-proportional hazards) and I'd really like to say that the same factor has a similar effect in the other

Dear All, Sorry to bother you again. I have a model: coxfita=coxph(Surv(rem.Remtime/365,rem.Rcens)~all.sex,data=nearma) and I'm trying to do a plot of Schoenfeld residuals using the code: plot(cox.zph(coxfita)) abline(h=0,lty=3) The error message I get is: Error in plot.window(...) : need finite 'ylim' values In addition: Warning messages: 1: In sqrt(x$var[i, i] * seval) : NaNs

Dear R-users, I am sorry if this is obvious. I am testing the proportional hazard assumptions using cox.zph. If i am not wrong, a g(t) function must be assumed. Four possibilities available in R are "km","identity" and "rank". may i know what functions of time are these transformation assuming? Thanks a lot in advance for your wisdom. kind regards, sing yee ling

Hello, I am hoping for some advice regarding warning/error messages I received when running a Cox regression # message 1 - obtained while creating a plot of residuals > plot (NV.zph, main = "groupNUSM - UNFIT", var= 'groupNUSM') Warning messages: 1: In approx(xx, xtime, seq(min(xx), max(xx), length.out = 17)[2 * : collapsing to unique 'x' values 2: In

The following works, you need to include x=TRUE in the call to coxph. Passing the time and status variables as additional arguments is a matter of personal preference. f.coxph.zph<-function(x, timeVar, statusVar) { cox.fit <- coxph(Surv(timeVar, statusVar) ~ x, na.action = na.exclude, method = "breslow", x=TRUE) fit.zph<-cox.zph(cox.fit) fit.zph$table[,3] } time.cox <-