rms v2.0-2

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rms Package

Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. rms is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new functions for binary and ordinal logistic regression models 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 logistic regression, 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.

Functions in rms

Name Description
anova.rms Analysis of Variance (Wald and F Statistics)
bj Buckley-James Multiple Regression Model
survfit.cph Cox Predicted Survival
predict.lrm Predicted Values for Binary and Ordinal Logistic Models
matinv Total and Partial Matrix Inversion using Gauss-Jordan Sweep Operator
psm Parametric Survival Model
rms rms Methods and Generic Functions
survplot Plot Survival Curves and Hazard Functions
fastbw Fast Backward Variable Selection
Glm rms Version of glm
Rq rms Package Interface to quantreg Package
summary.rms Summary of Effects in Model
groupkm Kaplan-Meier Estimates vs. a Continuous Variable
print.cph.fit Print cph.fit
residuals.lrm Residuals from a Logistic Regression Model Fit
Gls Fit Linear Model Using Generalized Least Squares
plot.Predict Plot Effects of Variables Estimated by a Regression Model Fit
residuals.ols Residuals for ols
ols Linear Model Estimation Using Ordinary Least Squares
pphsm Parametric Proportional Hazards form of AFT Models
datadist Distribution Summaries for Predictor Variables
robcov Robust Covariance Matrix Estimates
cr.setup Continuation Ratio Ordinal Logistic Setup
Function Compose an S Function to Compute X beta from a Fit
latexrms LaTeX Representation of a Fitted Model
survest.psm Parametric Survival Estimates
pentrace Trace AIC and BIC vs. Penalty
plot.xmean.ordinaly Plot Mean X vs. Ordinal Y
rms.trans rms Special Transformation Functions
lrm.fit Logistic Model Fitter
Predict Compute Predicted Values and Confidence Limits
val.prob Validate Predicted Probabilities
predab.resample Predictive Ability using Resampling
validate.ols Validation of an Ordinary Linear Model
rmsMisc Miscellaneous Design Attributes and Utility Functions
cph Cox Proportional Hazards Model and Extensions
validate.cph Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit
print.cph Print cph Results
validate Resampling Validation of a Fitted Model's Indexes of Fit
contrast.rms General Contrasts of Regression Coefficients
bplot 3-D Plots Showing Effects of Two Continuous Predictors in a Regression Model Fit
survfit.formula Compute a Survival Curve for Censored Data
validate.lrm Resampling Validation of a Logistic Model
gendata Generate Data Frame with Predictor Combinations
which.influence Which Observations are Influential
ie.setup Intervening Event Setup
bootcov Bootstrap Covariance and Distribution for Regression Coefficients
val.surv Validate Predicted Probabilities Against Observed Survival Times
rmsOverview Overview of rms Package
lrm Logistic Regression Model
validate.rpart Dxy and Mean Squared Error by Cross-validating a Tree Sequence
hazard.ratio.plot Hazard Ratio Plot
sensuc Sensitivity to Unmeasured Covariables
survest.cph Cox Survival Estimates
predictrms Predicted Values from Model Fit
print.ols Print ols
rms-internal Internal rms functions
specs.rms rms Specifications for Models
vif Variance Inflation Factors
residuals.cph Residuals for a cph Fit
calibrate Resampling Model Calibration
nomogram Draw a Nomogram Representing a Regression Fit
latex.cph LaTeX Representation of a Fitted Cox Model
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Details

Date 2009-09-07
License GPL (>= 2)
URL http://biostat.mc.vanderbilt.edu/rms
LazyLoad yes
Packaged 2009-09-07 19:44:13 UTC; harrelfe
Repository CRAN
Date/Publication 2009-09-07 22:27:34

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