similar to: coxph and survfit issue - strata

Dear All, I want to generate survival curve with cox model but I want to estimate the coefficients using glmnet. However, I also want to include a strata() term in the model. Could anyone please tell me how to have this strata() effect in the model in glmnet? I tried converting a formula with strata() to a design matrix and feeding to glmnet, but glmnet just treats the strata() term with one

Hi there, I perform a stratified cox and then I need the strata as a  numeric array "straft.ln" ft.ln <- coxph(Surv(times,deaths)~ages+chemos+chemos:f1+chemos:f2+horms+horms:f1+horms:f2+grades+grades:f1+grades:f2+positives+positives:f1+positives:f2+sizes+sizes:f1+sizes:f2+strata(stra),data=ddd) basehazzft.ln=basehaz(ft.ln,centered=FALSE) H0ft.ln=c(basehazzft.ln[,1])

First, here is your message as it appears on R-help. On 10/14/2012 05:00 AM, r-help-request@r-project.org wrote: > I?m trying to set up proportional hazard model that is stratified with > respect to covariate 1 and has an interaction between covariate 1 and > another variable, covariate 2. Both variables are categorical. In the > following, I try to illustrate the two problems that

I?m trying to set up proportional hazard model that is stratified with respect to covariate 1 and has an interaction between covariate 1 and another variable, covariate 2. Both variables are categorical. In the following, I try to illustrate the two problems that I?ve encountered, using the lung dataset. The first problem is the warning: To me, it seems that there are too many dummies

I am wondering how to estimate the survival curve for a particular case(s) given a coxph model using this example code: #fit a cox proportional hazards model and plot the #predicted survival curve fit <- coxph( Surv(futime,fustat)~resid.ds+strata(rx)+ecog.ps+age,data=ovarian[1:23,]) z <- survfit(fit,newdata=ovarian[24:26,],individual=F) zs <- z$surv zt <-

I have a model with quant vars only and the error message does not make sense: (mod1 <- coxph(Surv(time=strt,time2=stp,event=(resp==1))~ +incpost+I(amt/1e5)+rate+strata(termfac), subset=dt<"2010-08-30", data=inc,method="efron")) Call: coxph(formula = Surv(time = strt, time2 = stp, event = (resp == 1)) ~ +incpost + I(amt/1e+05) + rate + strata(termfac),

Dear all, I'm having difficulty getting access to data generated by survfit and print.survfit when they are using with a Cox model (survfit.coxph). I would like to programmatically access the median survival time for each strata together with the 95% confidence interval. I can get it on screen, but can't get to it algorithmically. I found myself examining the source of print.survfit to

Dear useRs, What is the syntax to obtain survival curves for single strata on many subjects? I have a model based on Surv(time,response) object, so there is a single row per subject and no start,stop and no switching of strata. The newdata has many subjects and each subject has a strata and the survival based on the subject risk and the subject strata is needed. If I do newpred <-

Hello, I'm trying to estimate a Cox proportional hazard model with time-varying covariates using coxph. The parameter estimates are fine but there is something wrong with the survival curves I get with survfit (results are not plausible). Let me explain why I think something's wrong. To make sure I'm setting up my data correctly to estimate a model with time-varying covariates, I

fit <- coxph(Surv(futime,fustat)~ age +strata(rx), data=ovarian, subset=1:23) curves <- survfit(fit, newdata=ovarian[24:26,]) I don't think this is mentioned in the documentation (I'll have to fix that!), but subscripting works for survfit objects. In this case there are 2 strata and 3 subjects, and curves[1,2] will return the survival curve for strata 1,

[code]>require("survival") > coxph(Surv(futime,fustat)~age + strata(rx),ovarian) Call: coxph(formula = Surv(futime, fustat) ~ age + strata(rx), data = ovarian) coef exp(coef) se(coef) z p age 0.137 1.15 0.0474 2.9 0.0038 Likelihood ratio test=12.7 on 1 df, p=0.000368 n= 26, number of events= 12 > coxph(Surv(futime,fustat)~age, ovarian, subset=rx==1)

This works ok: > cox = coxph(surv ~ bucket*(today + accor + both) + activity, data = data) > fit = survfit(cox, newdata=data[1:100,]) but using strata leads to problems: > cox.s = coxph(surv ~ bucket*(today + accor + both) + strata(activity), > data = data) > fit.s = survfit(cox.s, newdata=data[1:100,]) Error in model.frame.default(data = data[1:100, ], formula = ~bucket + :

Hello, I'm using plot.survfit to plot cumulative incidence of an event. Essentially, my code boils down to: cox <-coxph(Surv(EVINF,STATUS) ~ strata(TREAT) + covariates, data=dat) surv <- survfit(cox) plot(surv,mark.time=F,fun="event") Follow-up time extends to 54 weeks, but the last event occurs at week 30, and no more people are censored in between. Is there a

Hi everyone, I'm doing some coxph() analyses with a large and complex dataset. The data was collected in different centers, so I am using strata(centers) to stratify the analysis. My main issue is, not all centers collected all the variables, so for a model such as: coxph(Surv(days, cancer) ~ varA + sex + strata(centers), data) I might have 1 or more centers that have NA for varA (in

hie when i use plot.survfit to plot more than one graph why I only see the last graph how do i see the other graphs.for example n=20 n1=n/2 n2=n/4 a11=4;a12=4 ;a21=4 ;a22=4 t1<-array(1,c(n1)) t2<-array(2,c(n1)) treatgrp=matrix(c(t1,t2))

Hello: So i've fit a hazard function to a set of data using kmfit<-survfit(Surv(int, event)~factor(cohort)) this factor variable, "cohort" has four levels so naturally the strata variable has 4 values. I can use this data to estimate the hazard rate haz<-n.event/n.risk and calculate the cumulative hazard function by H<--log(haz) Now, I would like to plot this

Hello R-help. I am trying to make a stacked barplot where the color of the sections of each bar depend on another variable. > myData[1:11,] score percent marker cellType Malignant 1 0 100.00000 ESR1 (ER) Bladder.M(5) TRUE 2 0 80.00000 PAX8 Bladder.M(5) TRUE 3 1 20.00000 PAX8 Bladder.M(5) TRUE 4 0 100.00000 ESR1 (ER) Brain.N(3) FALSE 5 0

Hi R-Helpers, I am having difficulty plotting a coxph model with two predictors. My predictors are "morder" (a factor with five levels where the mean of each level is plotted as a separate line) and tmean (continuous). When I run a model with just morder it is fine and the plot is fine. When I add tmean, the coxph model runs fine but this model will not plot and I receive an

It would be nice if the 00check.log file also included this part of the output: Running ?bladder.R? Comparing ?bladder.Rout? to ?bladder.Rout.save? ... OK Running ?book1.R? Comparing ?book1.Rout? to ?book1.Rout.save? ... OK Running ?book2.R? Comparing ?book2.Rout? to ?book2.Rout.save? ... OK etc. The survival package has enough test scripts that it exceeds my terminal's scroll

Dear list members, I am working with a Cox ph model for the duration of unemployment. The event of interest in my analysis is getting employed. I have various background variables explaining this event: age, sex, education etc. I have multiple unemployment spells per person. I use a model with person-specific frailty terms in order to take into account the correlation of spells by the same