# rms v5.1-3

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## Regression Modeling Strategies

Regression modeling, testing, estimation, validation,
graphics, prediction, and typesetting by storing enhanced model design
attributes in the fit. 'rms' is a collection of functions that
assist with and streamline modeling. It also contains functions for
binary and ordinal logistic regression models, ordinal models for
continuous Y with a variety of distribution families, 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 regression
models, 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.

## Readme

# 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

- Overall: http://biostat.mc.vanderbilt.edu/Rrms
- Book: http://biostat.mc.vanderbilt.edu/rms
- CRAN: http://cran.r-project.org/web/packages/rms
- Changelog: https://github.com/harrelfe/rms/commits/master

# 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

## Functions in rms

Name | Description | |

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 | |

No Results! |

## Last month downloads

## Details

Date | 2019-01-27 |

License | GPL (>= 2) |

URL | http://biostat.mc.vanderbilt.edu/rms |

LazyLoad | yes |

NeedsCompilation | yes |

Packaged | 2019-01-27 16:33:33 UTC; harrelfe |

Repository | CRAN |

Date/Publication | 2019-01-27 17:40:03 UTC |

suggests | boot , plotly (>= 4.5.6) , tcltk |

depends | ggplot2 (>= 2.2) , Hmisc (>= 4.1-1) , lattice , SparseM , survival (>= 2.40-1) |

imports | htmlTable (>= 1.11.0) , htmltools , methods , multcomp , nlme (>= 3.1-123) , polspline , quantreg , rpart |

Contributors | Frank E Harrell Jr |

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