similar to: R-Help : Warning messages using plot(cox.zph)

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

Hi everybody, I want to do a contourplot in lattice with my raw data overlaid on it(xyplot) which seemed to be a very easy thing to do. I've tried it in many ways, but I haven't succeeded at obtaining it. let's say x, y, and z as the variables that comes from the data frame ''ex'': therefore my countourplot is as followed : contourplot(z ~ x * y, cuts=550) I

Hi everyone, Can anyone give me more details about the 'lp', 'risk', 'terms', and 'expected' options from the predict.coxph function? I actually found that risk is obtained from exp(lp). I can't find information on 'expected' type however. Is anybody can expand the information on this function? Thank you in advance, I will appreciate it.

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, 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

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

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 =

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 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

-- 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 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

Hi Guys, First, English is not my native language so sorry if the question is too difficult to understand. I can rephrase it if necessary. I have 32-bit Windows Xp SP3, i use R version 2.12.0 (2010-10-15), and the question is about Redundancy canonical analysis? plot problem in 3D using VEGAN, RGL, SCATTERPLOT3D and SFSMISC. I noticed the following? code to explain as clearly as possible the

>Hello, I am hoping for assistance in regards to examining the contribution of stratified variables in a cox regression. A previous post by Terry Therneau noted that "That is the point of a strata; you are declaring a variable to NOT be proportional hazards, and thus there is no single "hazard ratio" that describes it". Given this purpose of stratification, in the

This is a question about the use of the Cox proportional hazards model to analyze event histories. I am looking at the responses of sympathetic nervous system activity to a stimulus. The activity I observe is a burst that can only occur once per heart beat cycle (e.g., a binary count). Typically bursts occur in 60-80% of the heart cycles * sensory stimuli can modify these burst probabilities.

Hi, after standardizing my data by dividing each covariate by its mean, the hazard ratio of variables ranges btw ~ 0.5 and 3.55. when i test the PH assumption by cox.zph, rho ranges btw -0.4235863 and 0.359827. visualizing the PH assumption by plot, the plot of scaled schoefeld residuals against transformed time doesn't give a line with slope 0 for all covariates. note that there are 100

Dear R-help Community, I'm currently struggling with some issues extending the proportional Cox model with time-dependent coefficients and could really need some help. Since I'm not experienced in adding code in an email in a nice way I add the link to my question and code: https://stats.stackexchange.com/questions/297052/time-dependend-coefficients-in-a-cox-model Essentially, I try