rms v5.1-3.1
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 | |
contrast.rms | General Contrasts of Regression Coefficients | |
groupkm | Kaplan-Meier Estimates vs. a Continuous Variable | |
hazard.ratio.plot | Hazard Ratio Plot | |
plotp.Predict | Plot Effects of Variables Estimated by a Regression Model Fit Using plotly | |
pphsm | Parametric Proportional Hazards form of AFT Models | |
residuals.ols | Residuals for ols | |
rms-internal | Internal rms functions | |
survest.cph | Cox Survival Estimates | |
survest.psm | Parametric Survival Estimates | |
vif | Variance Inflation Factors | |
which.influence | Which Observations are Influential | |
Glm | rms Version of glm | |
Gls | Fit Linear Model Using Generalized Least Squares | |
gendata | Generate Data Frame with Predictor Combinations | |
ggplot.Predict | Plot Effects of Variables Estimated by a Regression Model Fit Using ggplot2 | |
latexrms | LaTeX Representation of a Fitted Model | |
lrm | Logistic Regression Model | |
predab.resample | Predictive Ability using Resampling | |
predict.lrm | Predicted Values for Binary and Ordinal Logistic Models | |
residuals.cph | Residuals for a cph Fit | |
ExProb | Function Generator For Exceedance Probabilities | |
Function | Compose an S Function to Compute X beta from a Fit | |
residuals.lrm | Residuals from an lrm or orm Fit | |
bplot | 3-D Plots Showing Effects of Two Continuous Predictors in a Regression Model Fit | |
calibrate | Resampling Model Calibration | |
rms | rms Methods and Generic Functions | |
rms.trans | rms Special Transformation Functions | |
validate | Resampling Validation of a Fitted Model's Indexes of Fit | |
validate.Rq | Validation of a Quantile Regression Model | |
sensuc | Sensitivity to Unmeasured Covariables | |
setPb | Progress Bar for Simulations | |
val.prob | Validate Predicted Probabilities | |
val.surv | Validate Predicted Probabilities Against Observed Survival Times | |
Predict | Compute Predicted Values and Confidence Limits | |
Rq | rms Package Interface to quantreg Package | |
nomogram | Draw a Nomogram Representing a Regression Fit | |
npsurv | Nonparametric Survival Estimates for Censored Data | |
ols | Linear Model Estimation Using Ordinary Least Squares | |
orm | Ordinal Regression Model | |
survfit.cph | Cox Predicted Survival | |
survplot | Plot Survival Curves and Hazard Functions | |
validate.ols | Validation of an Ordinary Linear Model | |
validate.rpart | Dxy and Mean Squared Error by Cross-validating a Tree Sequence | |
rmsOverview | Overview of rms Package | |
anova.rms | Analysis of Variance (Wald and F Statistics) | |
bj | Buckley-James Multiple Regression Model | |
cr.setup | Continuation Ratio Ordinal Logistic Setup | |
datadist | Distribution Summaries for Predictor Variables | |
ie.setup | Intervening Event Setup | |
latex.cph | LaTeX Representation of a Fitted Cox Model | |
orm.fit | Ordinal Regression Model Fitter | |
pentrace | Trace AIC and BIC vs. Penalty | |
predictrms | Predicted Values from Model Fit | |
print.cph | Print cph Results | |
specs.rms | rms Specifications for Models | |
summary.rms | Summary of Effects in Model | |
bootBCa | BCa Bootstrap on Existing Bootstrap Replicates | |
bootcov | Bootstrap Covariance and Distribution for Regression Coefficients | |
fastbw | Fast Backward Variable Selection | |
gIndex | Calculate Total and Partial g-indexes for an rms Fit | |
lrm.fit | Logistic Model Fitter | |
matinv | Total and Partial Matrix Inversion using Gauss-Jordan Sweep Operator | |
plot.Predict | Plot Effects of Variables Estimated by a Regression Model Fit | |
plot.xmean.ordinaly | Plot Mean X vs. Ordinal Y | |
print.ols | Print ols | |
psm | Parametric Survival Model | |
rmsMisc | Miscellaneous Design Attributes and Utility Functions | |
robcov | Robust Covariance Matrix Estimates | |
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 | |
cph | Cox Proportional Hazards Model and Extensions | |
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 | 2019-04-21 11:25:24 UTC; ripley |
Repository | CRAN |
Date/Publication | 2019-04-22 06:59:10 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 |
Include our badge in your README
[](http://www.rdocumentation.org/packages/rms)