similar to: Help on coxph

When adding a trend line to a scatterplot (e.g. abline (90,4,col="red"), I believe the "90" is the intercept and "4" is the slope. How do I determine the intercept and slope for the abline command? Kristopher R. Deininger Management Strategy & Entrepreneurship PhD Student 2012 Robert H. Smith School of Business University of Maryland 3330L Van Munching Hall

Hi! I'm trying to install centos 5.1 as a http installation from a centos mirror. i've done it before with Fedora, figured I could do it with Centos, too, but every time I try it, it goes all the way thru Anaconda to the point of entering the root password, then I get an error about not being able to find the repodata. I note that the section in the "upstream" manuals about

My question is, how to compute hazard function(H(t)) after building the coxph model. I even aware of the terminology that differs from hazard function(H(t)) and the hazard rate(h(t)). Here onward I wish to calculate both. Here what I have done in two different methods; ##########################################################################################

Hi, I am experimenting with using glht() from multcomp package together with coxph(), and glad to find that glht() can work on coph object, for example: > (fit<-coxph(Surv(stop, status>0)~treatment,bladder1)) coxph(formula = Surv(stop, status > 0) ~ treatment, data = bladder1) coef exp(coef) se(coef) z p treatmentpyridoxine -0.063 0.939 0.161

I am fitting a coxph model on a large dataset (approx 100,000 patients), and then trying to estimate the survival curves for several new patients based on the coxph object using survfit. When I run coxph I get the coxph object back fairly quickly however when I try to run survfit it does not come back. I am wondering if their is a more efficient way to get predicted survival curves from a coxph

Dear List, After including cluster() option the coxreg (from eha package) produces results slightly different than that of coxph (from survival) in the following time-dependent treatment effect calculation (example is used just to make the point). Will appreciate any explaination / comment. cheers, Ehsan ############################ require(survival) require(eha) data(heart) # create weights

Dear All: I have a question on using coxph for multiple genes: I have written code to loop through all 22283 genes in the Hgu-133A and apply coxph on survival data. However, I don't know how to work with the result for each gene: survtest<-coxph(Surv(pcc.primary.stg.3.cox[,'fup_interval'],pcc.primary.stg.

Dear all, The help file for the generic function vcov states "Classes with methods for this function include: 'lm', 'glm', 'nls', 'lme', 'gls', 'coxph' and 'survreg' (the last two in package 'survival')." Since, I am not able to use vcov.coxph(), I am wondering whether I am missing something (as I suspect..) regards, vito

I need to force a coxph() function in R to use a pre-calculated set of beta coefficients of a gene signature consisting of xx genes and the gene expression is also provided of those xx genes. If I try to use "coxph()" function in R using just the gene expression data alone, the beta coefficients and coxph$linear.predictors will change and I need to use the pre-calcuated linear predictor

I'm running multiple instances of ices. Also, I found what the problem was with the constant stream. I was getting a default stream because I was using my local ip address to run the server, and when I tried to access the different streams from my outside ip address something got confused. I'm running it from my outside ip address and everything works fine. Does anyone know a what to run

Hello - I am wanting to create some Cox PH models with coxph (in package survival) using different datasets. The code below illustrates my current approach and problem with completing this. ### BEGIN R SAMPLE CODE ############################## library(survival) #Define a function to make test data makeTestDF <- function(n) { times <- sample(1:200, n, replace = TRUE) event

Full_Name: John E. Kolassa Version: Version 1.8.1 OS: Solaris Submission from: (NULL) (128.6.76.36) Stepwise model selection for coxph appears to fail with method="exact". The code step(coxph(Surv(1:100,rep(1,100))~factor(rep(1:4,25)),method="exact")) produces the error message Start: AIC= 733.07 Surv(1:100, rep(1, 100)) ~ factor(rep(1:4, 25)) Error in

I tried to compare if cch() and coxph() can generate same result for same case cohort data Use the standard data in cch(): nwtco Since in cch contains the cohort size=4028, while ccoh.data size =1154 after selection, but coxph does not contain info of cohort size=4028. The rough estimate between coxph() and cch() is same, but the lower and upper CI and P-value are a little different. Can we

Dear List, Can anyone please explain the difference between cluster() and frailty() in a coxph? I am a bit puzzled about it. Would appreciate any useful reference or direction. cheers, Ehsan > marginal.model <- coxph(Surv(time, status) ~ rx + cluster(litter), rats) > frailty.model <- coxph(Surv(time, status) ~ rx + frailty(litter), rats) > marginal.model Call: coxph(formula =

Hi, I want to fit multiple cox models using the coxph() function. To do this, I use a for-loop and save the relevant results in a separate matrix. In the example below, only two models are fitted (my actual matrix has many more columns), one gives a warning message, while the other does not. Right now, I see all the warning message(s) after the for-loop is completed but have no idea which model

Hi, I am getting errors of the following kind. I can't seem to point the source of the error. I would greatly appreciate any advice. Many thanks and good day, -Melinda Error message : ---------------- "Ran out of iterations and did not converge in: fitter(X, Y, strats, offset, init, control, weights = weights,..." Details : --------- E is a vector of survival times (or censored

Hi all, I cant' wrap my head around an error from the coxph function (package survival). Here's an example: library(survival) n = 100; set.seed(1); time = rexp(n); event = sample(c(0,1), n, replace = TRUE) covar = data.frame(z = rnorm(n)); model = coxph(Surv(time, event)~ . , data = covar) R gives the following error: > model = coxph(Surv(time, event)~ . , data = covar) Error in

Hi, i need to use pspline. In this pspline function coxph.wtest was used. When I try to make some change to this function by pulling out the pspline function, it turns out R gave me an error msg, saying coxph.wtest cannot be found. Even if i dont change anything in pspline and just rename it and run the function, it did not work out. Can any one help me with this? is there anyway to get the

Hi, in coxph, coxph(Surv(time, status)~x,data=alm). How to encode x? For example, if x has two groups, the treatment group and control group. if I encode them as 1 and 2. Is the HR results treatment/control? What if I encode them as 0 and 1. I am confused with how survival package works for HR. What should I do to get a treatment/control HR? Thank you. -- View this message in context:

Dear R users, I noticed a problem in the anova command when applied on a single coxph object if there are missing observations in the data: This example code was run on R-2.6.1: > library(survival) > data(colon) > colondeath = colon[colon$etype==2, ] > m = coxph(Surv(time, status) ~ rx + sex + age + perfor, data=colondeath) > m Call: coxph(formula = Surv(time, status) ~ rx +