Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the BuckleyJames multiple regression model for rightcensored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the BuckleyJames model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
Package details 


Author  Frank E Harrell Jr <f.harrell@vanderbilt.edu> 
Date of publication  20170503 16:41:23 UTC 
Maintainer  Frank E Harrell Jr <f.harrell@vanderbilt.edu> 
License  GPL (>= 2) 
Version  5.11 
URL  http://biostat.mc.vanderbilt.edu/rms 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.