similar to: cox.zph

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

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

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

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

Dear R-users, I use the survsplit function in the survival package to change my data into counting-process format and the transformed format is as follow: (a) start stop event DP age .... 0 5 0 1 20 5 10 0 1 20 10 25 1 1 20 looking at the above three entries that belong to the same person, if an event happen at

Hi, I get a warning message when I plot cox.zph objects with the transform km and rank, but not with id and log with the same data set. Here's the command: example is a coxph object rk <- cox.zph(example, transform='rank') rk plot(rk) and here's the warning message: Warning messages: 1: suppression des ex-aequos de 'x' in: approx(xx, xtime, seq(min(xx), max(xx),

Dear R-users, I am checking the proportional hazard assumption of a cox model for a given covariate, let say Z1, after adjusting for other relavent covariates in the model. To this end, I fitted cox model stratified on the discrete values of Z1 and try to get beslow estimator for the baseline cumulative hazard function (H(t)) in each stratum. As far as i know, if the proportionality assumption

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

Hello, Excuse me for a more methodological than technical question. I'm developing a Cox model with 10 covariates. One of them is age (named "eta"). I've checked proportionality with cox.zph with age continuous: > cox.zph(coxph(Surv(TTP,CENSOTTP)~eta)) rho chisq p eta -0.0154 0.0225 0.88 and categorical (eta<60): >

Hello everyone! I am having some trouble supplying the gradient function to nlm in R for windows version 2.2.1. What follows are the R-code I use: fredcs39<-function(a1,b1,b2,x){return(a1+exp(b1+b2*x))} loglikcs39<-function(theta,len){ value<-sum(mcs39[1:len]*fredcs39(theta[1],theta[2],theta[3],c(8:(7+len))) - pcs39[1:len] * log(fredcs39(theta[1],theta[2],theta[3],c(8:(7+len)))))

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

> ... 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

What is the best way to report the standard error when publishing Kaplan-Meier plots? In my field (Vascular Surgery), practitioners loosely refer to the "10% error" cutoff as the point at which to stop drawing the KM curve. I am interpreting this as the *standard error of the cumulative hazard*, although I'm having a difficult time finding some guidelines about this (perhaps I am

Hi, I''m trying to share internet on a LAN I''ve a linux router with SQUID (with ZPH support) + FAIRNAT The idea is: - fairness sharing internet - priorize interactive traffic - if a web object is on squid-cache (HIT), user can download it, with a rate = LAN rate I''ve: - Last Fairnat Script: www.metamorpher.de/fairnat/ - SQUID 2.5STABLE5 with ZPH patch

Hi, I am using the Survival package, more precisely the cox.zph function, to plot log(Hazard rate) over time. if I type plot(temp.zph[2]) then I get the plot I want. However, I want to change the label of the y axis that cox.zph prints. plot(temp.zph[2],xlab='Days', ylab='log hazard for Fast recovery cluster') then I get Error in plot.default(range(xx), yr, type =

dear all, I would like to know whether survdiff and survReg function in the survival package work for left-truncated and right-censored data. If not, what other functions can i use to make comparison between two survival curves with LTRC data. thanks for any help given sing yee

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 R-users, I am trying to find the MLEs for a loglikelihood function (loglikcs39) and tried using both optim and nlm. fredcs39<-function(b1,b2,x){return(exp(b1+b2*x))} loglikcs39<-function(theta,len){ sum(mcs39[1:len]*fredcs39(theta[1],theta[2],c(8:(7+len))) - pcs39[1:len] * log(fredcs39(theta[1],theta[2],c(8:(7+len))))) } theta.start<-c(0.1,0.1) 1. The output from using optim is

Hi, I've been banging my head against the following problem for a while and thought the fine people on r-help might be able to help. I'm using the survival package. I'm studying the survival rate of a population with a preexisting linear-like event rate (there are theoretical reasons to believe it's linear, but of course it's subject to the usual sampling noise) Some of the

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