similar to: New version of rms package on CRAN

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

The rms ("Regression Modeling Strategies") package has undergone a massive update. The entire list of updates is at the bottom of this note. CRAN has the update for linux and will soon have it for Windows and Mac - check http://cran.r-project.org/web/packages/rms/ for availability. This rms update relies on a major update of the Hmisc package. The most user-visible changes are:

This is to announce a new package rms on CRAN. rms goes along with my book Regression Modeling Strategies. The home page for rms is http://biostat.mc.vanderbilt.edu/rms, or go directly to http://biostat.mc.vanderbilt.edu/Rrms for information just about the software. rms is a re-write of the Design package that has improved graphics and that duplicates very little code in the survival

This is to announce a new package rms on CRAN. rms goes along with my book Regression Modeling Strategies. The home page for rms is http://biostat.mc.vanderbilt.edu/rms, or go directly to http://biostat.mc.vanderbilt.edu/Rrms for information just about the software. rms is a re-write of the Design package that has improved graphics and that duplicates very little code in the survival

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

A new version of rms is now available on CRAN for Linux/UNIX. I expect Mac and Windows versions to be available in a day or so. This version works with and requires the newest version of Therneau's survival package. More information is at http://biostat.mc.vanderbilt.edu/Rrms Changes in version 3.2-0 (2011-02-14) * Changed to be compatible with survival 2.36-3 which is now required

A new version of rms is now available on CRAN for Linux/UNIX. I expect Mac and Windows versions to be available in a day or so. This version works with and requires the newest version of Therneau's survival package. More information is at http://biostat.mc.vanderbilt.edu/Rrms Changes in version 3.2-0 (2011-02-14) * Changed to be compatible with survival 2.36-3 which is now required

Hello, I would like to increase the number of iterations for running a Buckley-James regression model in the rms package, but something is apparently syntactically wrong. The following code initially is exactly as it appears in the help page (which runs successfully), then a "failure to converge" message (resulting from specifying an 'identity' link argument, the error message

Dear R-help, In the rms package, I have fitted an ols model with a variable represented as a restricted cubic spline, with the knot locations specified as a previously defined vector. When I save the model object and open it in another workspace which does not contain the vector of knot locations, I get an error message if I try to predict with that model. This also happens if only one workspace

1) Packages to be used- For smaller datasets use these 1. CAR Package http://cran.r-project.org/web/packages/car/index.html 2. GVLMA Package http://cran.r-project.org/web/packages/gvlma/index.html 3. ROCR Package http://rocr.bioinf.mpi-sb.mpg.de/ 4. Relaimpo Package 5. DAAG package 6. MASS package 7. Bootstrap package 8. Leaps package Also see

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,

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 All, I wonder if someone can point me in the right direction here. I'm working with the rms library, R 2.9.2 under Windows XP. I'm trying to arrange two plots side by side for a colleague. mfrow or mfcol do not seem to work, however, so I am obviously missing something important. I know that there have been changes in the graphics from Design to rms, but am just not sure where to

Dear R-users, I am using R 2.13.0 and rms 3.3-0 , but can not reproduce figure 7.8 of the handouts *Regression Modeling Strategies* ( http://biostat.mc.vanderbilt.edu/wiki/pub/Main/RmS/course2.pdf) by the following code. Could any one help me figure out how to solve this? setwd('C:/Rharrell') require(rms) load('data/counties.sav') older <- counties$age6574 + counties$age75

Greetings, I have the following problem: I want to compare a "parameter trajectory", i.e. a series of real numbers (representing equidistant samples of a time-varying parameter) produced by some "model", to a reference trajectory, measured from the real world, in order to get a rating of how good the model that produced the first trajectory is. Ok, so I use the RMS of the

Hi, I'm using the rms package to do regression analysis using the lrm function. Retrieving odds ratios is possible using summary.rms. However, I could not find any information on how exactly the odds ratios for continuous variables are calculated. It doesn't appear to be the odds ratio at 1 unit increase, because the output of summary.rms did not match the coefficient's value. E.g.

Hello, I am using Dr. Harrell's rms package to make a nomogram. I was able to make a beautiful one. However, I want to change 5-year survival probability to 5-year failure probability. I couldn?t get hazard rate from Hazard(f1) because I used cph for the model. Here is my code: library(rms) f1 <- cph(Surv(retime,dfs) ~ age+her2+t_stage+n_stage+er+grade+cytcyt+Cyt_PCDK2 , data=data11,