similar to: showing ticks for censored data in survfit() in the rms package

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"

Hi I am a new fan of R after getting mad with the graphical functional in SPSS. I have been able to create a nice looking Kaplan Meyer graph using Survplot function. However I have difficulties in turning the y axis to percent instead of the default 0-1 scale. Further I have tried the function yaxt="n" without any results. Any help in this matter will be appreciated. The code is

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,

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 <-

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

A major new version of the rms package is now on CRAN. The most user-visible changes are: - interactive plotly graphic methods for model fits. The best example of this is survplot for npsurv (Kaplan-Meier) estimates where the number of risk pop up as you hover over the curves, and you can click to bring up confidence bands for differences in survival curves - html methods for model fit

A major new version of the rms package is now on CRAN. The most user-visible changes are: - interactive plotly graphic methods for model fits. The best example of this is survplot for npsurv (Kaplan-Meier) estimates where the number of risk pop up as you hover over the curves, and you can click to bring up confidence bands for differences in survival curves - html methods for model fit

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

Hello,   does anyone have an example on how to use restricted cubic splines function rcs within survfit.cph, if cph (Cox Proportional Hazard Regression) was done with restricted cubic splines (which I made to work)? Thank you. > [[alternative HTML version deleted]]

I am cleaning up the rms package to not export functions not to be called directly by users. rms uses generic functions defined in other packages. For example there is a latex method in the Hmisc package, and rms has a latex method for objects of class "anova.rms" so there are anova.rms and latex.anova.rms functions in rms. I use:

Version 2.2-0 of the rms package is now available. This is a somewhat major update. One major change is not downward compatible: Instead of specifying predictor=. or predictor=NA to Predict, summary, nomogram, survplot, gendata, you just specify the name of the predictor. For example, to get predictions for the default range of x1 and for just 2 values of x2 you might specify Predict(fit,

Version 2.2-0 of the rms package is now available. This is a somewhat major update. One major change is not downward compatible: Instead of specifying predictor=. or predictor=NA to Predict, summary, nomogram, survplot, gendata, you just specify the name of the predictor. For example, to get predictions for the default range of x1 and for just 2 values of x2 you might specify Predict(fit,

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

A new version of rms is now available on CRAN for Linux and Windows (Mac will probably be available very soon). Largest changes include latex methods for validate.* and adding the capability to force a subset of variables to be included in all backwards stepdown models (single model or validation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if

A new version of rms is now available on CRAN for Linux and Windows (Mac will probably be available very soon). Largest changes include latex methods for validate.* and adding the capability to force a subset of variables to be included in all backwards stepdown models (single model or validation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if

rms version 3.3-1 has been installed on CRAN. New features/bug fixes are below. * Added new example for anova.rms for making dot plots of partial R^2 of predictors * Defined logLik.ols (calls logLik.lm) * Fixed and cleaned up logLik.rms, AIC.rms * Fixed residuals.psm to allow other type= values used by residuals.survreg * Fixed Predict and survplot.rms to allow for case

CRAN has a significant update to rms. Windows and unix/linux versions are available and I expect the Mac version to be available soon. The most significant improvement is addition of latex=TRUE arguments to model fitting print methods, made especially for use with Sweave. Here is a summary of changes since the previous version. Changes in version 3.1-0 (2010-09-12) * Fixed gIndex to not

CRAN has a significant update to rms. Windows and unix/linux versions are available and I expect the Mac version to be available soon. The most significant improvement is addition of latex=TRUE arguments to model fitting print methods, made especially for use with Sweave. Here is a summary of changes since the previous version. Changes in version 3.1-0 (2010-09-12) * Fixed gIndex to not

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

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