similar to: help--Cox ph model

I'm doing prediction of the survival cases using gene expression profiles(Affymetrix chips). Can somebody tell me how to use the Cox PH model to select genes and make a prediction of survival? Thanks. Guangchun

I try to do single proportion test on my category data. Here is my R script: library("ctest") catSignifTest <- function( catFile ) { ############################################################### ## Get the data sets from text file catData <- read.table( catFile ) ncols <- length(catData) nrows <- length(catData[,1]) ncol1 <- ncols - 1 probeNbr

Dear R-users/helpers, Does anyone tell me how to retrieve the data frame column names? I'm working on coxph model to analyze survival data of Affy DNA chips. I get the coxph coef p-value for each probe and want output the probe name with the p-value. The probe names are the data frame column names. How can I do this? Thanks for your help. Guangchun

Always reply to the list. I do not do private consulting. (I have cc'ed this to the list). I still think this belongs on stackexchange, not r-help. I think you need to read up on the mathematics of spline bases. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his

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

Hello, I want to generate data set from Cox PH model with gamma frailty effects. theta(parameter for frailty distribution)=2 beta=1.5 n=300 cluster size=30 number of clusters=10 I think I should first generate u from Gamma(Theta,theta) and then using this theta I could not decide how I should generate the survival times? Is there any package for this? or any document you could suggest? Any

Hi All, I'm learning the R codes for Cox PH modeling. Could I ask you what the function of "factor" in modeling? Thank you! When dealing with the categorical covariates (for example 3 groups), it will come out different results if we add the command "factor" in front of the categorical covariate or not: if we don't add "factor", there is only one

Dear R-list users, I am trying to do simulation of survival data to enable it to run under frailty option. Below is the function a that I am using. My questions are: 1. How do I modify it to get bigger (hopefully significant) value of Variance of random effect? 2. What changes do I have to make in the function to run it under correlated frailty model? (may be in kinship package) 3. Is there

Hi All, I have a left truncated, right censored cox model: coxph(Surv(start, stop, censor) ~ x + y, mydata) I would like to know how much of the observed variance (as a number between 0 and 1) is explained by each variable. How could I do that? Adding terms sequentially and then using anova(mod1, mod2) tells me whether I get a significant improvement of the fit, but does not tell me how much

Hello all, I am a medical student and as a capstone for my summer research project I am going to create a simple online web "calculator" for users to input their relevant data, and a probability of relapse within 5 years will be computed and returned based on the Cox PH model I have developed. The issue I'm having is finding a definitive method/function to feed the user's

Here is an example of how to do it. > library(survival) > vfit <- coxph(Surv(time, status) ~ celltype + trt, data=veteran) > userinput <- data.frame(celltype="smallcell", trt = 1) > usercurve <- survfit(vfit, newdata=userinput) #the entire predicted survival curve > user2 <- summary(usercurve, time= 2*365.25) # 2 year time point > user2$surv [1]

Hello all, thanks for your time and patience. I'm looking for a method in R to analyse the following data: Time to waking after anaesthetic for medical procedures repeated on the same individual. > str(mysurv) labelled [1:740, 1:2] 20 20 15 20 30+ 40+ 50 30 15 10 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr [1:2] "time" "status" -

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.

Dear all, I would like to know if it is possible to fit in R a Cox ph model with time-dependent covariates and to account for hierarchical effects at the same time. Additionally, I'd like also to know if it would be possible to perform any feature selection on this model fit. I have a data set that is composed by multiple marker measurements (and hundreds of covariates) at different time

Hi, Can anybody tell me what the message below means and how to overcome it. Thanks, Neil Warning message: X matrix deemed to be singular; variable 2 in: coxph(Surv(age_at_death, death) ~ project$pluralgp + project$yrborn + ......... >

Hi, I'm using a Cox-Regression to estimate hazard rates on prepayments. I'm using the "pspline" function to face non-linearity, but I have no clue how to interpret the result. Unfortunately I did not find enough information on the "pspline" function wether in the survival package nor using google.. I got following output: * library(survival)* > > > >

Target: FreeBSD 6.2-STABLE on i386 autoconf says: configure:2122: checking build system type configure:2140: result: i386-unknown-freebsd6.2 [...] configure:2721: gcc -v >&5 Using built-in specs. Configured with: FreeBSD/i386 system compiler Thread model: posix gcc version 3.4.6 [FreeBSD] 20060305 [...] objdir != srcdir, for both llvm and gcc. Release build. llvm-gcc 4.2 from source.

Hello: In the example below (or for a censored data) using survfit.coxph, can anyone point me to a link or a pdf as to how the probabilities appearing in bold under "summary(pred$surv)" are calculated? Do these represent acumulative probability distribution in time (not including censored time)? Thanks very much, parmee *fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)*

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Dear R users, I am doing Cox regression using coxph(Survival) or cph(Design). I have time varying effects (diagnosed with schoenfeld residuals Chi2 test and graph) so I first want to split time into 2 separate intervals : t<6months and t>=6months, to estimate one hazard ratio (hr) for each interval. I am analysing Overall survival according to 3 prognostic factors (age,deep,ldh).