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rms
View on CRAN: Click
here
Download and install rms package within the R console
Install from CRAN:
install.packages("rms")
Install from Github:
library("remotes")
install_github("cran/rms")
Install by package version:
library("remotes")
install_version("rms", "7.0-0")
Attach the package and use:
library("rms")
Maintained by
Frank E Harrell Jr
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
rmsb . 10.32614/CRAN.package.rms . https://hbiostat.org/R/rms/ . https://github.com/harrelfe/rms . rms results . rms.pdf . rms_7.0-0.tar.gz . rms_7.0-0.zip . rms_7.0-0.zip . rms_6.8-1.zip . rms_7.0-0.tgz . rms_7.0-0.tgz . rms_6.8-1.tgz . rms_7.0-0.tgz . rms_7.0-0.tgz . rms_6.8-1.tgz . rms archive . rmsb . base.rms . rmsMD . https://CRAN.R-project.org/package=rms .
First Published: 2009-09-08
Latest Update: 2023-09-12
Description:
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.
How to cite:
Frank E Harrell Jr (2009). rms: Regression Modeling Strategies. R package version 7.0-0, https://cran.r-project.org/web/packages/rms. Accessed 26 Mar. 2025.
Previous versions and publish date:
2.0-2 (2009-09-08 00:28), 2.1-0 (2009-10-05 17:04), 2.2-0 (2010-02-24 09:17), 3.0-0 (2010-05-16 18:21), 3.1-0 (2010-09-13 09:13), 3.2-0 (2011-02-17 14:08), 3.3-0 (2011-02-28 16:06), 3.3-1 (2011-06-01 18:31), 3.3-2 (2011-11-10 13:59), 3.3-3 (2011-12-12 08:15), 3.4-0 (2012-01-17 15:41), 3.5-0 (2012-03-24 23:40), 3.6-0 (2012-10-30 14:51), 3.6-2 (2012-12-11 18:32), 3.6-3 (2013-01-11 19:15), 4.0-0 (2013-07-11 13:47), 4.1-0 (2013-12-05 18:03), 4.1-1 (2014-01-22 20:45), 4.1-2 (2014-02-28 23:32), 4.1-3 (2014-03-02 16:38), 4.2-0 (2014-04-13 23:11), 4.2-1 (2014-09-19 00:44), 4.3-0 (2015-02-16 07:10), 4.3-1 (2015-05-01 01:36), 4.4-0 (2015-09-28 17:02), 4.4-1 (2015-12-21 21:34), 4.4-2 (2016-02-21 19:52), 4.5-0 (2016-04-04 08:37), 5.0-0 (2016-11-03 10:55), 5.0-1 (2016-12-08 14:42), 5.1-0 (2017-01-01 23:44), 5.1-1 (2017-05-03 18:41), 5.1-2 (2018-01-07 23:27), 5.1-3.1 (2019-04-22 08:59), 5.1-3 (2019-01-27 18:40), 5.1-4 (2019-11-17 15:30), 6.0-0 (2020-06-04 22:40), 6.0-1 (2020-07-18 07:50), 6.1-0 (2020-11-29 15:10), 6.1-1 (2021-02-06 21:50), 6.2-0 (2021-03-18 07:50), 6.3-0 (2022-04-22 15:20), 6.4-0 (2023-01-15 15:40), 6.4-1 (2023-01-23 01:30), 6.5-0 (2023-02-09 16:10), 6.6-0 (2023-04-09 20:10), 6.7-0 (2023-05-08 16:30), 6.7-1 (2023-09-12 05:50), 6.8-0 (2024-03-11 17:20), 6.8-1 (2024-05-27 14:00), 6.8-2 (2024-08-23 07:10), 6.9-0 (2024-12-12 15:00)
Other packages that cited rms R package
View rms citation profile
Other R packages that rms depends,
imports, suggests or enhances
Complete documentation for rms
Functions, R codes and Examples using
the rms R package
Some associated functions: ExProb . Function . Glm . Gls . LRupdate . Predict . Rq . Xcontrast . anova.rms . bj . bootBCa . bootcov . bplot . calibrate . contrast . cph . cr.setup . datadist . fastbw . gIndex . gendata . ggplot.Predict . groupkm . hazard.ratio.plot . ie.setup . impactPO . importexport . latex.cph . latexrms . lrm.fit.bare . lrm.fit . lrm . matinv . nomogram . npsurv . ols . orm.fit . orm . pentrace . plot.Predict . plot.contrast.rms . plot.xmean.ordinaly . plotp.Predict . poma . pphsm . predab.resample . predict.lrm . predictrms . print.Glm . print.cph . print.impactPO . print.ols . prmiInfo . processMI.fit.mult.impute . processMI . psm . residuals.Glm . residuals.cph . residuals.lrm . residuals.ols . rms-internal . rms . rms.trans . rmsMisc . robcov . sensuc . setPb . specs.rms . summary.rms . survest.cph . survest.psm . survfit.cph . survplot . val.prob . val.surv . validate.Rq . validate.cph . validate.lrm . validate . validate.ols . validate.rpart . vif . which.influence . zzzrmsOverview .
Some associated R codes: Full rms package functions and examples
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