# rms v5.1-4

Monthly downloads

## 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 | |

Gls | Fit Linear Model Using Generalized Least Squares | |

ExProb | Function Generator For Exceedance Probabilities | |

Glm | rms Version of glm | |

Rq | rms Package Interface to quantreg Package | |

Predict | Compute Predicted Values and Confidence Limits | |

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

bootcov | Bootstrap Covariance and Distribution for Regression Coefficients | |

bootBCa | BCa Bootstrap on Existing Bootstrap Replicates | |

bj | Buckley-James Multiple Regression Model | |

anova.rms | Analysis of Variance (Wald and F Statistics) | |

fastbw | Fast Backward Variable Selection | |

cr.setup | Continuation Ratio Ordinal Logistic Setup | |

cph | Cox Proportional Hazards Model and Extensions | |

contrast.rms | General Contrasts of Regression Coefficients | |

gIndex | Calculate Total and Partial g-indexes for an rms Fit | |

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

calibrate | Resampling Model Calibration | |

datadist | Distribution Summaries for Predictor Variables | |

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 | |

latexrms | LaTeX Representation of a Fitted Model | |

groupkm | Kaplan-Meier Estimates vs. a Continuous Variable | |

ie.setup | Intervening Event Setup | |

hazard.ratio.plot | Hazard Ratio Plot | |

lrm.fit | Logistic Model Fitter | |

matinv | Total and Partial Matrix Inversion using Gauss-Jordan Sweep Operator | |

latex.cph | LaTeX Representation of a Fitted Cox Model | |

nomogram | Draw a Nomogram Representing a Regression Fit | |

ols | Linear Model Estimation Using Ordinary Least Squares | |

orm | Ordinal Regression Model | |

npsurv | Nonparametric Survival Estimates for Censored Data | |

predict.lrm | Predicted Values for Binary and Ordinal Logistic Models | |

predab.resample | Predictive Ability using Resampling | |

pentrace | Trace AIC and BIC vs. Penalty | |

orm.fit | Ordinal Regression Model Fitter | |

plot.xmean.ordinaly | Plot Mean X vs. Ordinal Y | |

plot.Predict | Plot Effects of Variables Estimated by a Regression Model Fit | |

psm | Parametric Survival Model | |

print.ols | Print ols | |

predictrms | Predicted Values from Model Fit | |

residuals.ols | Residuals for ols | |

residuals.cph | Residuals for a cph Fit | |

rms-internal | Internal rms functions | |

setPb | Progress Bar for Simulations | |

sensuc | Sensitivity to Unmeasured Covariables | |

print.cph | Print cph Results | |

survplot | Plot Survival Curves and Hazard Functions | |

plotp.Predict | Plot Effects of Variables Estimated by a Regression Model Fit Using plotly | |

survfit.cph | Cox Predicted Survival | |

residuals.lrm | Residuals from an lrm or orm Fit | |

specs.rms | rms Specifications for Models | |

val.prob | Validate Predicted Probabilities | |

val.surv | Validate Predicted Probabilities Against Observed Survival Times | |

summary.rms | Summary of Effects in Model | |

rmsOverview | Overview of rms Package | |

survest.cph | Cox Survival Estimates | |

survest.psm | Parametric Survival Estimates | |

validate.Rq | Validation of a Quantile Regression Model | |

validate | Resampling Validation of a Fitted Model's Indexes of Fit | |

pphsm | Parametric Proportional Hazards form of AFT Models | |

vif | Variance Inflation Factors | |

which.influence | Which Observations are Influential | |

rms | rms Methods and Generic Functions | |

validate.rpart | Dxy and Mean Squared Error by Cross-validating a Tree Sequence | |

validate.ols | Validation of an Ordinary Linear Model | |

rms.trans | rms Special Transformation Functions | |

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

robcov | Robust Covariance Matrix Estimates | |

validate.lrm | Resampling Validation of a Logistic or Ordinal Regression Model | |

rmsMisc | Miscellaneous Design Attributes and Utility Functions | |

No Results! |

## Last month downloads

## Details

Date | 2019-11-16 |

License | GPL (>= 2) |

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

LazyLoad | yes |

NeedsCompilation | yes |

Packaged | 2019-11-17 02:38:23 UTC; harrelfe |

Repository | CRAN |

Date/Publication | 2019-11-17 14:30:03 UTC |

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

depends | ggplot2 (>= 2.2) , Hmisc (>= 4.3-0) , lattice , R (>= 3.5.0) , SparseM , survival (>= 3.1-6) |

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

Contributors | Frank E Harrell Jr |

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