similar to: Design Survplot performance

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,

Hello , I am hoping for some advice regarding obtaining the values for the hazard function in a cox regression that I have undertaken. I have a model in the following form, analysed with the package survival (v. 2.34-1) and a log-log plot obtained using Design (v. 2.1-2). For two variables, the lines in the survival curves crossed. The statistician I been obtaining advice from (who does not

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

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

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 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)

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

I am trying to figure out how to apply a loglog link to a binomial model (dichotomous response variable with far more zeros than ones). I am aware that there are several relevant posts on this list, but I am afraid I need a little more help. The two suggested approaches seem to be: 1) modify the make.link function in GLM, or 2) use the loglog or cloglog functions in the VGAM package.

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 would like to do an R glm() with family = binomial(link="loglog") Right now, the cloglog link exists, which is nice when the data have a heavy tail to the left. I have the opposite case and the loglog link is what I need. Can someone suggest how to add the loglog link onto glm()? It would be lovely to have it there by default, and it certainly makes sense to have the two opposite

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:

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

Hi, I wish to write a new link function for a GLM. R's glm routine does not supply the "loglog" link. I modified the make.link function adding the code: }, loglog = { linkfun <- function(mu) -log(-log(mu)) linkinv <- function(eta) exp(-exp(-eta)) mu.eta <- function(eta) exp(-exp(-eta)-eta) valideta <- function(eta) all(eta != 0)

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 have data on a single variable LOGT. It has about 300,000 observations. I am trying to make a Histogram out of this data set. Following is my effort. Could anyone help me to solve this error. > hist(x) Error in hist.default(x) : `x' must be numeric > class(x) [1] "data.frame" > is.object(x) [1] TRUE > is.vector(x) [1] FALSE > is.numeric(x) [1] FALSE >

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 all, A looong time ago, Witold Eryk Wolski asked here why there wasn't a log="xy" parameter to the hist() function <URL:http://www.R-project.org/nocvs/mail/r-help/2001/0267.html>, and Prof. Ripley responded that a loglog histogram does not make much sense, and that one should use a better density estimate if one seeks to plot log density. I understand the point and I

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

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