similar to: Survplot, Y-axis in percent

Hi Dear R-users I have a database with 18000 observations and 20 variables. I am running cox regression on five variables and trying to use survfit to plot the survival based on a specific variable without success. Lets say I have the following coxph: >library(survival) >fit <- coxph(Surv(futime, fustat) ~ age + rx, data = ovarian) >fit what I am trying to do is plot a survival

Dear R users, I know one way to see the code for a hidden function, say function_x, is using default.function_x (e.g. summary.default). But how can I see the code for imported packages that have no namespace (in this case Design)? Many Thanks Eleni

Hello, I apologize for the post as I am certainly overlooking a simple solution to my difficulties with getting a legend to print on a survplot from the rms package. I am plotting the following: survplot(survest(fita), n.risk=T, conf='none', cex.n.risk=.85, dots=T, col='gray10', lty=2) survplot(survest(fit), n.risk=F, conf='none', add=T) survplot(survest(fitb), n.risk=F,

Dear R-help How can one get survplot() to place the number at risk just below the survival curve as opposed to the default which is just above the x-axis? I tried the code bellow but the result is not satisfactory as some numbers are repeated several times at different y coordinates and the position of the n.risk numbers corresponds to the x-axis tick marks not the survival curve time of

Hi, I have a Cox PH model that's large for my server, 120K rows, ~300 factors with 3 levels each, so about 1000 columns. The 300 factors all pass a preliminary test of association with the outcome. Solving this with cph from Design takes about 3 hours. I have created the fit with x=T, y=T to save the model data. I want to validate the PH assumption by calling survplot(fit, gender=NA,

Dear R-helpers I am wondering if there is an option to the survplot function in the design package that allows for drawing Kaplan-Meier plots starting from 0 instead of 1, similar like fun = 'event' in the standard plotting function used on a survfit object. I apologize in advance for having missed any obvious informational sources but I really didn't find anything in the

Dear all, I am trying to plot KM curves with confidence bands with function survplot under package rms. However, the following codes do not seem to work. The KM curves are produced, but the confidence bands are not there. Any insights? Thanks in advance. library(rms) ########data generation############ n <- 1000 set.seed(731) age <- 50 + 12*rnorm(n) label(age) <- "Age"

Dear useRs, I was asked to produce a survival curve like this: http://www.palug.net/Members/jabba/immaginetta.png/view with the cardinality of the riskset at the bottom. I do not like doing it, because it doesn't add any valuable information and because it doesn't discriminate between died and censored. Nevertheless, is there someone able to tell me how to do it? Currently the only

Hi, in Design package, a plot of survival probability vs. a covariate can be generated by survplot() on a cph object using the folliowing code: n <- 1000 set.seed(731) age <- 50 + 12*rnorm(n) label(age) <- "Age" sex <- factor(sample(c('male','female'), n, TRUE)) cens <- 15*runif(n) h <- .02*exp(.04*(age-50)+.8*(sex=='Female')) dt <-

deaR user, I found an unexpected behaviour of the rms::survplot.survfit function, that is giving me inverted labels for the patient-at-risk rows. The problem is that, for some reason, the survival::summary.survfit function changes the order of two of the suvfit object's strata when called (on my dataset) with the times= option (is this another unexpected behaviour?). survplot takes the

Dear R users, Please can you help me with a relatively straightforward problem that I am struggling with? I am simply trying to plot a baseline survivor and hazard function for a simple data set of lung cancer survival where `futime' is follow up time in months and status is 1=dead and 0=alive. Using the survival package: lung.wbs <- survreg( Surv(futime, status)~ 1, data=lung,

Hello, I write to know how can I modify the x axis : when I plot a survival object, R plots a graph with x values = 0, 10, 20, 30 while I want a graph with values 0, 6, 12, 18, 24 in the x axis. How can I do this? In R 2.1.1 version there was "time.inc" in survplot, but in version R 2.2.0 there isn't it! I am sorry for my english and I hope that you understand my problem. Thank you

R-ers! Referees demand that the line in the KM-curve should be changed to dotted at the point where standarerror is <= 10 %. I don't think it's a good habit but I urgently need to implement such a thing in R with survfit, survplot or another program. They also want numbers at risk below the curve Some help, please.... Fredrik ######################## Fredrik Lundgren

I am using the package Design for survival analysis. I want to plot a simple Kaplan-Meier fit of survival vs. age, with age grouped as quantiles. I can do this: survplot(survfit(Surv(time,status) ~ cut(age,3), data=veteran) but I would like to do something like this: survplot(survfit(Surv(time,status) ~ quantile(age,3), data=veteran) #will not work ideally I would like to superimpose

The answer to this may be obvious, but I was wondering in the rms package and the survfit(), how you can plot the censored time points as ticks. Take for example, library(survival) library(rms) foo <- data.frame(Time=c(1,2,3,4,5,6,10), Status=c(1,1,0,0,1,1,1)) answer <- survfit(Surv(foo$Time, foo$Status==1) ~1) # this shows the censored time points as ticks at Time = 3 and 4 plot(answer)

Dear experts, I would like to know how to plot the log-minus-log plot for survival analysis (to check the proportional assumption) in R. Using the AML example. fit <- survfit(Surv(time, status) ~ x, data=aml) length(fit$surv) #20 as the length of fit$surv is shorter than aml$x and aml$time. I don't know how to plot. Thank you. Regards, CH -- CH Chan Research Assistant - KWH

I am using plot(survfit(Surv(time,status) ~...) and would like to add error bars rather than the confidence intervals. Am I able to do this at specified times? e.g. when time = 20 & 40. leukemia.surv <- survfit(Surv(time, status) ~ x, data = aml) plot(leukemia.surv, lty = 2:3,xlim = c(0,50)) #can i add error bars at times 20 & 40? legend(100, .9, c("Maintenance", "No

Good afternoon, I am currently trying to do some work on survival analysis. - I hope to seek your advice re: 2 questions (1 general and 1 specific) (1) I'm trying to do a stratified Cox analysis and subsequently plot(survfit(object)). It seems to work for some strata, but not for others. I have tumor grade, which is a range of 1 - 4. When I divide this range of 1:4 into 2 groups, it

Dear list, does anyone know of a R-package that has implemented the increasingly popular inclusion of the number of patients at risk below Kaplan-Meier curves like in http://bloodjournal.hematologylibrary.org/content/vol116/issue19/images/large/zh89991058760001.jpeg any hint (or negative answer) is much appreciated. Thanks Thorsten -- Thorsten Raff 2nd Medical Department, University

Dear UseR, I do not know if this a problem with me, my data or cph/survest in package design. The example below works with a standard data set, but not with my data, but I cannot locate the problem. Note that I am using an older package of survival to avoid a problem with the newly renamed function in survival meeting Design. Dieter # First, check standard example to make sure library(Design)