# 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 | |

No Results! |

## Last month downloads

## 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 |

depends | Hmisc (>= 3.7) , survival |

suggests | lattice , nlme , quantreg , rpart |

Contributors | Frank E Harrell Jr |

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