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rms

Regression Modeling Strategies

Current Goals

  • A non-downward compatible change will occur in the next release of the package
  • The survfit.formula function (seen by the user as just survfit) for obtaining nonparametric survival estimates will be replaced by the npsurv function
  • The purpose is to avoid conflicts with the survival package
  • survfit.coxph has a new id option that generalizes individual=TRUE; need to change survfit.cph and survest.cph to use that

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

38,030

Version

5.1-3

License

GPL (>= 2)

Maintainer

Frank E Harrell Jr

Last Published

January 27th, 2019

Functions in rms (5.1-3)

gendata

Generate Data Frame with Predictor Combinations
npsurv

Nonparametric Survival Estimates for Censored Data
contrast.rms

General Contrasts of Regression Coefficients
print.ols

Print ols
plot.xmean.ordinaly

Plot Mean X vs. Ordinal Y
residuals.lrm

Residuals from an lrm or orm Fit
ggplot.Predict

Plot Effects of Variables Estimated by a Regression Model Fit Using ggplot2
residuals.cph

Residuals for a cph Fit
nomogram

Draw a Nomogram Representing a Regression Fit
plot.Predict

Plot Effects of Variables Estimated by a Regression Model Fit
cr.setup

Continuation Ratio Ordinal Logistic Setup
fastbw

Fast Backward Variable Selection
datadist

Distribution Summaries for Predictor Variables
ie.setup

Intervening Event Setup
bj

Buckley-James Multiple Regression Model
gIndex

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

LaTeX Representation of a Fitted Model
cph

Cox Proportional Hazards Model and Extensions
psm

Parametric Survival Model
lrm

Logistic Regression Model
survest.cph

Cox Survival Estimates
rmsMisc

Miscellaneous Design Attributes and Utility Functions
groupkm

Kaplan-Meier Estimates vs. a Continuous Variable
survest.psm

Parametric Survival Estimates
bplot

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

Robust Covariance Matrix Estimates
lrm.fit

Logistic Model Fitter
calibrate

Resampling Model Calibration
validate.ols

Validation of an Ordinary Linear Model
validate.rpart

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

Variance Inflation Factors
which.influence

Which Observations are Influential
plotp.Predict

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

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

Parametric Proportional Hazards form of AFT Models
rms

rms Methods and Generic Functions
predab.resample

Predictive Ability using Resampling
predict.lrm

Predicted Values for Binary and Ordinal Logistic Models
latex.cph

LaTeX Representation of a Fitted Cox Model
orm.fit

Ordinal Regression Model Fitter
predictrms

Predicted Values from Model Fit
rms.trans

rms Special Transformation Functions
hazard.ratio.plot

Hazard Ratio Plot
pentrace

Trace AIC and BIC vs. Penalty
ols

Linear Model Estimation Using Ordinary Least Squares
print.cph

Print cph Results
residuals.ols

Residuals for ols
setPb

Progress Bar for Simulations
survplot

Plot Survival Curves and Hazard Functions
orm

Ordinal Regression Model
sensuc

Sensitivity to Unmeasured Covariables
val.prob

Validate Predicted Probabilities
rms-internal

Internal rms functions
specs.rms

rms Specifications for Models
val.surv

Validate Predicted Probabilities Against Observed Survival Times
summary.rms

Summary of Effects in Model
validate

Resampling Validation of a Fitted Model's Indexes of Fit
validate.Rq

Validation of a Quantile Regression Model
validate.cph

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

Resampling Validation of a Logistic or Ordinal Regression Model
rmsOverview

Overview of rms Package
ExProb

Function Generator For Exceedance Probabilities
Glm

rms Version of glm
Function

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

Fit Linear Model Using Generalized Least Squares
bootBCa

BCa Bootstrap on Existing Bootstrap Replicates
anova.rms

Analysis of Variance (Wald and F Statistics)
Predict

Compute Predicted Values and Confidence Limits
bootcov

Bootstrap Covariance and Distribution for Regression Coefficients
Rq

rms Package Interface to quantreg Package
survfit.cph

Cox Predicted Survival