rms
Regression Modeling Strategies
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.
- Version6.8-2
- R version≥ 4.4.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release08/23/2024
Documentation
Team
Frank E Harrell Jr
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- Depends1 package
- Imports15 packages
- Suggests8 packages
- Reverse Depends11 packages
- Reverse Imports52 packages
- Reverse Suggests30 packages
- Reverse Enhances2 packages