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Regression Modeling Strategies
Frank E Harrell Jr <>
GPL (>= 2)
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 Buckley-James multiple regression model for right-censored 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 Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
Package Version Released
rms 4.0-0 2 years 13 weeks ago
rms 3.6-3 2 years 39 weeks ago
rms 3.6-2 2 years 43 weeks ago
rms 3.6-0 2 years 49 weeks ago
rms 3.5-0 3 years 29 weeks ago
rms 3.4-0 3 years 38 weeks ago
rms 3.3-3 3 years 43 weeks ago
rms 3.3-2 3 years 48 weeks ago
rms 3.3-1 4 years 19 weeks ago
rms 3.3-0 4 years 32 weeks ago
Your rating: None Overall: 5 (21 votes)
Your rating: None Documentation: 5 (21 votes)