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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

29,222

Version

6.2-0

License

GPL (>= 2)

Issues

Pull Requests

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Last Published

March 18th, 2021

Functions in rms (6.2-0)

anova.rms

Analysis of Variance (Wald and F Statistics)
bj

Buckley-James Multiple Regression Model
contrast.rms

General Contrasts of Regression Coefficients
cph

Cox Proportional Hazards Model and Extensions
Rq

rms Package Interface to quantreg Package
Predict

Compute Predicted Values and Confidence Limits
groupkm

Kaplan-Meier Estimates vs. a Continuous Variable
hazard.ratio.plot

Hazard Ratio Plot
survfit.cph

Cox Predicted Survival
rms.trans

rms Special Transformation Functions
residuals.lrm

Residuals from an lrm or orm Fit
rms

rms Methods and Generic Functions
residuals.cph

Residuals for a cph Fit
fastbw

Fast Backward Variable Selection
survplot

Plot Survival Curves and Hazard Functions
gIndex

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

BCa Bootstrap on Existing Bootstrap Replicates
ie.setup

Intervening Event Setup
latex.cph

LaTeX Representation of a Fitted Cox Model
bootcov

Bootstrap Covariance and Distribution for Regression Coefficients
plotp.Predict

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

Function Generator For Exceedance Probabilities
cr.setup

Continuation Ratio Ordinal Logistic Setup
lrm.fit.bare

lrm.fit.bare
datadist

Distribution Summaries for Predictor Variables
lrm.fit

Logistic Model Fitter
Function

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

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

Parametric Proportional Hazards form of AFT Models
npsurv

Nonparametric Survival Estimates for Censored Data
predab.resample

Predictive Ability using Resampling
ols

Linear Model Estimation Using Ordinary Least Squares
residuals.ols

Residuals for ols
print.ols

Print ols
psm

Parametric Survival Model
rmsMisc

Miscellaneous Design Attributes and Utility Functions
rmsOverview

Overview of rms Package
survest.psm

Parametric Survival Estimates
robcov

Robust Covariance Matrix Estimates
survest.cph

Cox Survival Estimates
rms-internal

Internal rms functions
validate

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

Fit Linear Model Using Generalized Least Squares
Glm

rms Version of glm
validate.Rq

Validation of a Quantile Regression Model
gendata

Generate Data Frame with Predictor Combinations
ggplot.Predict

Plot Effects of Variables Estimated by a Regression Model Fit Using ggplot2
lrm

Logistic Regression Model
plot.contrast.rms

plot.contrast.rms
bplot

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

Resampling Model Calibration
latexrms

LaTeX Representation of a Fitted Model
print.Glm

print.glm
print.cph

Print cph Results
sensuc

Sensitivity to Unmeasured Covariables
plot.xmean.ordinaly

Plot Mean X vs. Ordinal Y
setPb

Progress Bar for Simulations
matinv

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

Ordinal Regression Model
pentrace

Trace AIC and BIC vs. Penalty
nomogram

Draw a Nomogram Representing a Regression Fit
plot.Predict

Plot Effects of Variables Estimated by a Regression Model Fit
validate.cph

Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit
predict.lrm

Predicted Values for Binary and Ordinal Logistic Models
orm.fit

Ordinal Regression Model Fitter
predictrms

Predicted Values from Model Fit
specs.rms

rms Specifications for Models
summary.rms

Summary of Effects in Model
validate.lrm

Resampling Validation of a Logistic or Ordinal Regression Model
which.influence

Which Observations are Influential
vif

Variance Inflation Factors
val.surv

Validate Predicted Probabilities Against Observed Survival Times
validate.ols

Validation of an Ordinary Linear Model
val.prob

Validate Predicted Probabilities
validate.rpart

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