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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", "6.8-0")
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
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 6.8-0, https://cran.r-project.org/web/packages/rms
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)
Other packages that cited rms R package
View rms citation profile
Other R packages that rms depends,
imports, suggests or enhances
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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