similar to: New version of rms package on CRAN

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:

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 lists, I want to write a function of a vector and reverse the order of its elements. Here is my code: revector<-function(n){ y=vector(length=n) for(i in n:1){ y[i]=i } return(y) } i want my output to be like this: y [1] 10 9 8 7 6 5 4 3 2 1 Any suggestion?? Thanks!! Cheers, Anisah ---------------------------------

Hmisc 4.0-0 is now on CRAN. The package has undergone a massive update. The most user-visable changes are; - support for Rmarkdown html notebooks - advanced html tables using the htmlTable package and summaryM function; can copy and paste into word processors - support for plotly interactive graphics, e.g. options(grType='plotly') plot(describe(mydata)) - new function

Hmisc 4.0-0 is now on CRAN. The package has undergone a massive update. The most user-visable changes are; - support for Rmarkdown html notebooks - advanced html tables using the htmlTable package and summaryM function; can copy and paste into word processors - support for plotly interactive graphics, e.g. options(grType='plotly') plot(describe(mydata)) - new function

Dear list, I was wondering if there is a function to plot league tables, sometimes also known as "caterpillar plots"? A league table is conceptually very similar to a box plot. One difference is that the inter-quartile ranges are not shown. If there isn't such a function a first attempt for a "selfmade" plot would be to tell boxplot not to plot boxes (sounds silly

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

This is a question of clarification. IN 2009 Higgins, Thompson and Spiegelhalter (J R Statist Soc A 172:137-159) gave WinBUGs code to get credible intervals from random effects meta analysis for the prediction interval of a new study. It appears that the predict.rma function creates approximate credible intervals (pending a function revision by the author) for that purpose. Is my assumption

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

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

How can I extract the adjusted R^2 value from an ols object (using rms package)? library(rms) x <- rnorm(10) y <- x + rnorm(10) ols1 <- ols(y ~ x) Typing "ols1" displays adjusted R^2 among other things, but how can I assign it to a variable? I tried str(ols1) but couldn't see where to go from there. Thanks, Mark Seeto

The integration of plot methods for various outputs from rms packages is a great appreciated aspect of the rms package. I particularly like to use: plot(summary(model)) for my own purposes, but... for publication/presentation I need to modify details like variable names, or the number of signficant digits used in the figure annotations. Is there a simple way to modify the plot inputs

Hi I am trying to install "rms" package but while installing it shows following error package 'survival' 2.36-2 is loaded, but >= 2.36.3 is required by 'rms' what to do? i am using linux OS I have tried by updated r-base-core but it didnt work regards GRR [[alternative HTML version deleted]]

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)

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 fellow R-users, I?m using the Glm function (gamma family of distributions) from the rms package to compare 2 groups on costs data. Although the summary function does provide the mean cost difference and standard errors, I believe these values were in the (natural) log ratio format. Is there a function to express these values into the original scale of the response variable (i.e., dollars)