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rms

Regression Modeling Strategies

Current Goals

  • Implement estimation and prediction methods for the Bayesian partial proportional odds model blrm function

Web Sites

To Do

  • Fix survplot so that explicitly named adjust-to values are still in subtitles. See tests/cph2.s.
  • Fix fit.mult.impute to average sigma^2 and then take square root, instead of averaging sigma
  • Implement user-added distributions in psm - see https://github.com/harrelfe/rms/issues/41

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Version

Install

install.packages('rms')

Monthly Downloads

36,249

Version

8.1-1

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Frank Harrell Jr

Last Published

February 18th, 2026

Functions in rms (8.1-1)

LRupdate

LRupdate
Ocens

Censored Ordinal Variable
ExProb

Function Generators For Exceedance and Survival Probabilities
Ocens2Surv

Ocens2Surv
Ocens2ord

Recode Censored Ordinal Variable
Olinks

Likehood-Based Statistics for Other Links for orm Fits
Gls

Fit Linear Model Using Generalized Least Squares
Predict

Compute Predicted Values and Confidence Limits
Glm

rms Version of glm
Function

Compose an S Function to Compute X beta from a Fit
Punits

Prepare units for Printing and Plotting
as.data.frame.Ocens

Convert `Ocens` Object to Data Frame to Facilitate Subset
adapt_orm

Adaptive orm Fit For a Single Continuous Predictor
Xcontrast

Xcontrast
Rq

rms Package Interface to quantreg Package
bootBCa

BCa Bootstrap on Existing Bootstrap Replicates
anova.rms

Analysis of Variance (Wald, LR, and F Statistics)
bplot

3-D Plots Showing Effects of Two Continuous Predictors in a Regression Model Fit
bj

Buckley-James Multiple Regression Model
bootcov

Bootstrap Covariance and Distribution for Regression Coefficients
ggplot.Predict

Plot Effects of Variables Estimated by a Regression Model Fit Using ggplot2
ggplot.npsurv

Title Plot npsurv Nonparametric Survival Curves Using ggplot2
gIndex

Calculate Total and Partial g-indexes for an rms Fit
gendata

Generate Data Frame with Predictor Combinations
calibrate

Resampling Model Calibration
cph

Cox Proportional Hazards Model and Extensions
datadist

Distribution Summaries for Predictor Variables
cr.setup

Continuation Ratio Ordinal Logistic Setup
fastbw

Fast Backward Variable Selection
contrast.rms

General Contrasts of Regression Coefficients
infoMxop

Operate on Information Matrices
ie.setup

Intervening Event Setup
importedexported

Exported Functions That Were Imported From Other Packages
intCalibration

Check Parallelism Assumption of Ordinal Semiparametric Models
is.na.Ocens

is.na Method for Ocens Objects
hazard.ratio.plot

Hazard Ratio Plot
impactPO

Impact of Proportional Odds Assumpton
latexrms

LaTeX Representation of a Fitted Model
latex.cph

LaTeX Representation of a Fitted Cox Model
groupkm

Kaplan-Meier Estimates vs. a Continuous Variable
ordESS

ordESS
ordParallel

Check Parallelism Assumption of Ordinal Semiparametric Models
npsurv

Nonparametric Survival Estimates for Censored Data
ols

Linear Model Estimation Using Ordinary Least Squares
matinv

Total and Partial Matrix Inversion using Gauss-Jordan Sweep Operator
orm.fit

Ordinal Regression Model Fitter
nomogram

Draw a Nomogram Representing a Regression Fit
lrm.fit

lrm.fit
lrm

Logistic Regression Model
orm

Ordinal Regression Model
plot.contrast.rms

plot.contrast.rms
plot.rexVar

plot.rexVar
plotIntercepts

Plot Intercepts
plot.xmean.ordinaly

Plot Mean X vs. Ordinal Y
plotp.Predict

Plot Effects of Variables Estimated by a Regression Model Fit Using plotly
pentrace

Trace AIC and BIC vs. Penalty
poma

Examine proportional odds and parallelism assumptions of `orm` and `lrm` model fits.
predab.resample

Predictive Ability using Resampling
plot.Predict

Plot Effects of Variables Estimated by a Regression Model Fit
pphsm

Parametric Proportional Hazards form of AFT Models
prmiInfo

prmiInfo
print.rexVar

print.rexVar
print.impactPO

Print Result from impactPO
print.cph

Print cph Results
print.Ocens

print Method for Ocens Objects
processMI

processMI
print.Glm

print.glm
print.ols

Print ols
predictrms

Predicted Values from Model Fit
predict.lrm

Predicted Values for Binary and Ordinal Logistic Models
processMI.fit.mult.impute

processMI.fit.mult.impute
residuals.ols

Residuals for ols
rexVar

rexVar
recode2integer

recode2integer
residuals.Glm

residuals.Glm
residuals.cph

Residuals for a cph Fit
rms-internal

Internal rms functions
residuals.lrm

Residuals from an lrm or orm Fit
rms

rms Methods and Generic Functions
psm

Parametric Survival Model
[.Ocens

Ocens
survest.orm

Title survest.orm
summary.rms

Summary of Effects in Model
setPb

Progress Bar for Simulations
rms.trans

rms Special Transformation Functions
rmsMisc

Miscellaneous Design Attributes and Utility Functions
sensuc

Sensitivity to Unmeasured Covariables
specs.rms

rms Specifications for Models
survest.cph

Cox Survival Estimates
robcov

Robust Covariance Matrix Estimates
survplot.orm

Title Survival Curve Plotting
survfit.cph

Cox Predicted Survival
validate.cph

Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit
survest.psm

Parametric Survival Estimates
val.prob

Validate Predicted Probabilities
validate.Rq

Validation of a Quantile Regression Model
validate.lrm

Resampling Validation of a Logistic or Ordinal Regression Model
validate

Resampling Validation of a Fitted Model's Indexes of Fit
survplot

Plot Survival Curves and Hazard Functions
val.surv

Validate Predicted Probabilities Against Observed Survival Times
vif

Variance Inflation Factors
rmsOverview

Overview of rms Package
validate.ols

Validation of an Ordinary Linear Model
validate.rpart

Dxy and Mean Squared Error by Cross-validating a Tree Sequence
which.influence

Which Observations are Influential