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  "Date": "2026-05-10",
  "Title": "Regression Modeling Strategies",
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  "Description": "Regression modeling, testing, estimation, validation,\ngraphics, prediction, and typesetting by storing enhanced model\ndesign attributes in the fit.  'rms' is a collection of\nfunctions that assist with and streamline modeling.  It also\ncontains functions for binary and ordinal logistic regression\nmodels, ordinal models for continuous Y with a variety of\ndistribution families, and the Buckley-James multiple\nregression model for right-censored responses, and implements\npenalized maximum likelihood estimation for logistic and\nordinary linear models.  'rms' works with almost any regression\nmodel, but it was especially written to work with binary or\nordinal regression models, Cox regression, accelerated failure\ntime models, ordinary linear models, the Buckley-James model,\ngeneralized least squares for serially or spatially correlated\nobservations, generalized linear models, and quantile\nregression.",
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    "ols",
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    "oos.loglik",
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    "val.surv",
    "validate",
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    "Xcontrast"
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      "title": "Analysis of Variance (Wald, LR, and F Statistics)",
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        "plot.anova.rms",
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      "title": "Buckley-James Multiple Regression Model",
      "topics": [
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        "bj.fit",
        "bjplot",
        "print.bj",
        "residuals.bj",
        "validate.bj"
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        "calibrate.default",
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        "calibrate.psm",
        "plot.calibrate",
        "plot.calibrate.default",
        "print.calibrate",
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    {
      "page": "cph",
      "title": "Cox Proportional Hazards Model and Extensions",
      "topics": [
        "cph",
        "Mean.cph",
        "Quantile.cph",
        "Survival.cph"
      ]
    },
    {
      "page": "cr.setup",
      "title": "Continuation Ratio Ordinal Logistic Setup",
      "concept": [
        "logistic regression model",
        "continuation ratio model",
        "ordinal logistic model",
        "ordinal response"
      ],
      "topics": [
        "cr.setup"
      ]
    },
    {
      "page": "datadist",
      "title": "Distribution Summaries for Predictor Variables",
      "topics": [
        "datadist",
        "print.datadist"
      ]
    },
    {
      "page": "ExProb",
      "title": "Function Generators For Exceedance and Survival Probabilities",
      "topics": [
        "ExProb",
        "ExProb.orm",
        "plot.ExProb",
        "Survival.orm"
      ]
    },
    {
      "page": "fastbw",
      "title": "Fast Backward Variable Selection",
      "concept": [
        "stepwise",
        "variable selection"
      ],
      "topics": [
        "fastbw",
        "print.fastbw"
      ]
    },
    {
      "page": "Function",
      "title": "Compose an S Function to Compute X beta from a Fit",
      "concept": [
        "logistic regression model"
      ],
      "topics": [
        "Function.cph",
        "Function.rms",
        "perlcode",
        "sascode"
      ]
    },
    {
      "page": "gendata",
      "title": "Generate Data Frame with Predictor Combinations",
      "topics": [
        "gendata"
      ]
    },
    {
      "page": "ggplot.npsurv",
      "title": "Title Plot npsurv Nonparametric Survival Curves Using ggplot2",
      "topics": [
        "ggplot.npsurv"
      ]
    },
    {
      "page": "ggplot.Predict",
      "title": "Plot Effects of Variables Estimated by a Regression Model Fit Using ggplot2",
      "topics": [
        "ggplot.Predict"
      ]
    },
    {
      "page": "gIndex",
      "title": "Calculate Total and Partial g-indexes for an rms Fit",
      "topics": [
        "gIndex",
        "plot.gIndex",
        "print.gIndex"
      ]
    },
    {
      "page": "Glm",
      "title": "rms Version of glm",
      "topics": [
        "Glm"
      ]
    },
    {
      "page": "Gls",
      "title": "Fit Linear Model Using Generalized Least Squares",
      "topics": [
        "Gls",
        "print.Gls"
      ]
    },
    {
      "page": "groupkm",
      "title": "Kaplan-Meier Estimates vs. a Continuous Variable",
      "concept": [
        "grouping",
        "stratification",
        "aggregation"
      ],
      "topics": [
        "groupkm"
      ]
    },
    {
      "page": "hazard.ratio.plot",
      "title": "Hazard Ratio Plot",
      "topics": [
        "hazard.ratio.plot"
      ]
    },
    {
      "page": "ie.setup",
      "title": "Intervening Event Setup",
      "topics": [
        "ie.setup"
      ]
    },
    {
      "page": "impactPO",
      "title": "Impact of Proportional Odds Assumpton",
      "topics": [
        "impactPO"
      ]
    },
    {
      "page": "importexport",
      "title": "Exported Functions That Were Imported From Other Packages",
      "topics": [
        "ggplot",
        "Surv"
      ]
    },
    {
      "page": "infoMxop",
      "title": "Operate on Information Matrices",
      "topics": [
        "infoMxop"
      ]
    },
    {
      "page": "intCalibration",
      "title": "Check Parallelism Assumption of Ordinal Semiparametric Models",
      "topics": [
        "intCalibration"
      ]
    },
    {
      "page": "is.na.Ocens",
      "title": "is.na Method for Ocens Objects",
      "topics": [
        "is.na.Ocens"
      ]
    },
    {
      "page": "latex.cph",
      "title": "LaTeX Representation of a Fitted Cox Model",
      "topics": [
        "latex.cph",
        "latex.lrm",
        "latex.ols",
        "latex.orm",
        "latex.pphsm",
        "latex.psm"
      ]
    },
    {
      "page": "latexrms",
      "title": "LaTeX Representation of a Fitted Model",
      "topics": [
        "latex.bj",
        "latex.Glm",
        "latex.Gls",
        "latexrms"
      ]
    },
    {
      "page": "lrm",
      "title": "Logistic Regression Model",
      "concept": [
        "logistic regression model",
        "ordinal logistic model",
        "proportional odds model",
        "continuation ratio model",
        "ordinal response"
      ],
      "topics": [
        "lrm",
        "print.lrm"
      ]
    },
    {
      "page": "lrm.fit",
      "title": "lrm.fit",
      "topics": [
        "lrm.fit"
      ]
    },
    {
      "page": "LRupdate",
      "title": "LRupdate",
      "topics": [
        "LRupdate"
      ]
    },
    {
      "page": "matinv",
      "title": "Total and Partial Matrix Inversion using Gauss-Jordan Sweep Operator",
      "topics": [
        "matinv"
      ]
    },
    {
      "page": "nomogram",
      "title": "Draw a Nomogram Representing a Regression Fit",
      "topics": [
        "legend.nomabbrev",
        "nomogram",
        "plot.nomogram",
        "print.nomogram"
      ]
    },
    {
      "page": "npsurv",
      "title": "Nonparametric Survival Estimates for Censored Data",
      "topics": [
        "npsurv"
      ]
    },
    {
      "page": "Ocens",
      "title": "Censored Ordinal Variable",
      "topics": [
        "Ocens"
      ]
    },
    {
      "page": "Ocens2ord",
      "title": "Recode Censored Ordinal Variable",
      "topics": [
        "Ocens2ord"
      ]
    },
    {
      "page": "Ocens2Surv",
      "title": "Ocens2Surv",
      "topics": [
        "Ocens2Surv"
      ]
    },
    {
      "page": "Olinks",
      "title": "Likehood-Based Statistics for Other Links for orm Fits",
      "topics": [
        "Olinks"
      ]
    },
    {
      "page": "ols",
      "title": "Linear Model Estimation Using Ordinary Least Squares",
      "topics": [
        "ols"
      ]
    },
    {
      "page": "ordESS",
      "title": "ordESS",
      "topics": [
        "ordESS"
      ]
    },
    {
      "page": "ordParallel",
      "title": "Check Parallelism Assumption of Ordinal Semiparametric Models",
      "topics": [
        "ordParallel"
      ]
    },
    {
      "page": "orm",
      "title": "Ordinal Regression Model",
      "concept": [
        "logistic regression model",
        "ordinal logistic model",
        "proportional odds model",
        "ordinal response"
      ],
      "topics": [
        "orm",
        "print.orm",
        "Quantile.orm"
      ]
    },
    {
      "page": "orm.fit",
      "title": "Ordinal Regression Model Fitter",
      "concept": [
        "logistic regression model"
      ],
      "topics": [
        "orm.fit"
      ]
    },
    {
      "page": "pentrace",
      "title": "Trace AIC and BIC vs. Penalty",
      "concept": [
        "logistic regression model",
        "penalized MLE",
        "ridge regression",
        "shrinkage"
      ],
      "topics": [
        "effective.df",
        "pentrace",
        "plot.pentrace",
        "print.pentrace"
      ]
    },
    {
      "page": "plot.contrast.rms",
      "title": "plot.contrast.rms",
      "topics": [
        "plot.contrast.rms"
      ]
    },
    {
      "page": "plot.Predict",
      "title": "Plot Effects of Variables Estimated by a Regression Model Fit",
      "topics": [
        "pantext",
        "plot.Predict"
      ]
    },
    {
      "page": "plot.rexVar",
      "title": "plot.rexVar",
      "topics": [
        "plot.rexVar"
      ]
    },
    {
      "page": "plot.xmean.ordinaly",
      "title": "Plot Mean X vs. Ordinal Y",
      "concept": [
        "model validation",
        "logistic regression model"
      ],
      "topics": [
        "plot.xmean.ordinaly"
      ]
    },
    {
      "page": "plotIntercepts",
      "title": "Plot Intercepts",
      "topics": [
        "plotIntercepts"
      ]
    },
    {
      "page": "plotp.Predict",
      "title": "Plot Effects of Variables Estimated by a Regression Model Fit Using plotly",
      "topics": [
        "plotp.Predict"
      ]
    },
    {
      "page": "poma",
      "title": "Examine proportional odds and parallelism assumptions of `orm` and `lrm` model fits.",
      "topics": [
        "poma"
      ]
    },
    {
      "page": "pphsm",
      "title": "Parametric Proportional Hazards form of AFT Models",
      "topics": [
        "pphsm",
        "print.pphsm",
        "vcov.pphsm"
      ]
    },
    {
      "page": "predab.resample",
      "title": "Predictive Ability using Resampling",
      "concept": [
        "model validation",
        "bootstrap",
        "predictive accuracy"
      ],
      "topics": [
        "predab.resample"
      ]
    },
    {
      "page": "Predict",
      "title": "Compute Predicted Values and Confidence Limits",
      "topics": [
        "Predict",
        "print.Predict",
        "rbind.Predict"
      ]
    },
    {
      "page": "predict.lrm",
      "title": "Predicted Values for Binary and Ordinal Logistic Models",
      "concept": [
        "logistic regression model"
      ],
      "topics": [
        "Mean.lrm",
        "Mean.orm",
        "predict.lrm",
        "predict.orm"
      ]
    },
    {
      "page": "predictrms",
      "title": "Predicted Values from Model Fit",
      "topics": [
        "predict.bj",
        "predict.cph",
        "predict.Glm",
        "predict.Gls",
        "predict.ols",
        "predict.psm",
        "predict.rms",
        "predictrms"
      ]
    },
    {
      "page": "print.cph",
      "title": "Print cph Results",
      "topics": [
        "print.cph"
      ]
    },
    {
      "page": "print.Glm",
      "title": "print.glm",
      "topics": [
        "print.Glm"
      ]
    },
    {
      "page": "print.impactPO",
      "title": "Print Result from impactPO",
      "topics": [
        "print.impactPO"
      ]
    },
    {
      "page": "print.Ocens",
      "title": "print Method for Ocens Objects",
      "topics": [
        "print.Ocens"
      ]
    },
    {
      "page": "print.ols",
      "title": "Print ols",
      "topics": [
        "print.ols"
      ]
    },
    {
      "page": "print.rexVar",
      "title": "print.rexVar",
      "topics": [
        "print.rexVar"
      ]
    },
    {
      "page": "prmiInfo",
      "title": "prmiInfo",
      "topics": [
        "prmiInfo"
      ]
    },
    {
      "page": "processMI",
      "title": "processMI",
      "topics": [
        "processMI"
      ]
    },
    {
      "page": "processMI.fit.mult.impute",
      "title": "processMI.fit.mult.impute",
      "topics": [
        "processMI.fit.mult.impute"
      ]
    },
    {
      "page": "psm",
      "title": "Parametric Survival Model",
      "topics": [
        "Hazard",
        "Hazard.psm",
        "lines.residuals.psm.censored.normalized",
        "Mean.psm",
        "print.psm",
        "psm",
        "Quantile.psm",
        "residuals.psm",
        "Survival",
        "Survival.psm",
        "survplot.residuals.psm.censored.normalized"
      ]
    },
    {
      "page": "Punits",
      "title": "Prepare units for Printing and Plotting",
      "topics": [
        "Punits"
      ]
    },
    {
      "page": "recode2integer",
      "title": "recode2integer",
      "topics": [
        "recode2integer"
      ]
    },
    {
      "page": "residuals.cph",
      "title": "Residuals for a cph Fit",
      "concept": [
        "model validation"
      ],
      "topics": [
        "residuals.cph"
      ]
    },
    {
      "page": "residuals.Glm",
      "title": "residuals.Glm",
      "topics": [
        "residuals.Glm"
      ]
    },
    {
      "page": "residuals.lrm",
      "title": "Residuals from an 'lrm' or 'orm' Fit",
      "concept": [
        "logistic regression model",
        "model validation"
      ],
      "topics": [
        "plot.lrm.partial",
        "residuals.lrm",
        "residuals.orm"
      ]
    },
    {
      "page": "residuals.ols",
      "title": "Residuals for ols",
      "concept": [
        "model validation"
      ],
      "topics": [
        "residuals.ols"
      ]
    },
    {
      "page": "rexVar",
      "title": "rexVar",
      "topics": [
        "rexVar"
      ]
    },
    {
      "page": "rms",
      "title": "rms Methods and Generic Functions",
      "concept": [
        "logistic regression model"
      ],
      "topics": [
        "Design",
        "modelData",
        "rms"
      ]
    },
    {
      "page": "rms.trans",
      "title": "rms Special Transformation Functions",
      "concept": [
        "logistic regression model",
        "transformation"
      ],
      "topics": [
        "%ia%",
        "asis",
        "catg",
        "gTrans",
        "lsp",
        "makepredictcall.rms",
        "matrx",
        "pol",
        "rcs",
        "rms.trans",
        "scored",
        "strat"
      ]
    },
    {
      "page": "rmsMisc",
      "title": "Miscellaneous Design Attributes and Utility Functions",
      "topics": [
        "AIC.rms",
        "calibrate.rms",
        "combineRelatedPredictors",
        "DesignAssign",
        "formatNP",
        "Getlim",
        "Getlimi",
        "html.naprint.delete",
        "interactions.containing",
        "latex.naprint.delete",
        "logLik.Gls",
        "logLik.ols",
        "logLik.rms",
        "lrtest",
        "Newlabels",
        "Newlabels.rms",
        "Newlevels",
        "Newlevels.rms",
        "nobs.rms",
        "oos.loglik",
        "oos.loglik.cph",
        "oos.loglik.Glm",
        "oos.loglik.lrm",
        "oos.loglik.ols",
        "oos.loglik.psm",
        "param.order",
        "Penalty.matrix",
        "Penalty.setup",
        "print.lrtest",
        "print.rms",
        "prModFit",
        "prStats",
        "related.predictors",
        "reListclean",
        "removeFormulaTerms",
        "rmsArgs",
        "rmsMisc",
        "survest.rms",
        "univarLR",
        "vcov.cph",
        "vcov.Glm",
        "vcov.Gls",
        "vcov.lrm",
        "vcov.ols",
        "vcov.orm",
        "vcov.psm",
        "vcov.rms"
      ]
    },
    {
      "page": "zzzrmsOverview",
      "title": "Overview of rms Package",
      "concept": [
        "overview"
      ],
      "topics": [
        "rms.Overview",
        "rmsOverview"
      ]
    },
    {
      "page": "robcov",
      "title": "Robust Covariance Matrix Estimates",
      "concept": [
        "cluster sampling",
        "intra-class correlation"
      ],
      "topics": [
        "robcov"
      ]
    },
    {
      "page": "Rq",
      "title": "rms Package Interface to quantreg Package",
      "topics": [
        "latex.Rq",
        "predict.Rq",
        "print.Rq",
        "Rq",
        "RqFit"
      ]
    },
    {
      "page": "sensuc",
      "title": "Sensitivity to Unmeasured Covariables",
      "concept": [
        "model validation",
        "sampling",
        "logistic regression model",
        "sensitivity analysis"
      ],
      "topics": [
        "plot.sensuc",
        "sensuc"
      ]
    },
    {
      "page": "setPb",
      "title": "Progress Bar for Simulations",
      "topics": [
        "setPb"
      ]
    },
    {
      "page": "specs.rms",
      "title": "rms Specifications for Models",
      "topics": [
        "print.specs.rms",
        "specs",
        "specs.rms"
      ]
    },
    {
      "page": "summary.rms",
      "title": "Summary of Effects in Model",
      "concept": [
        "logistic regression model"
      ],
      "topics": [
        "html.summary.rms",
        "latex.summary.rms",
        "plot.summary.rms",
        "print.summary.rms",
        "summary.rms"
      ]
    },
    {
      "page": "survest.cph",
      "title": "Cox Survival Estimates",
      "topics": [
        "survest",
        "survest.cph"
      ]
    },
    {
      "page": "survest.orm",
      "title": "Title survest.orm",
      "topics": [
        "survest.orm"
      ]
    },
    {
      "page": "survest.psm",
      "title": "Parametric Survival Estimates",
      "topics": [
        "print.survest.psm",
        "survest.psm"
      ]
    },
    {
      "page": "survfit.cph",
      "title": "Cox Predicted Survival",
      "topics": [
        "survfit.cph"
      ]
    },
    {
      "page": "survplot",
      "title": "Plot Survival Curves and Hazard Functions",
      "topics": [
        "survdiffplot",
        "survplot",
        "survplot.npsurv",
        "survplot.rms",
        "survplotp",
        "survplotp.npsurv"
      ]
    },
    {
      "page": "survplot.orm",
      "title": "Title Survival Curve Plotting",
      "topics": [
        "survplot.orm"
      ]
    },
    {
      "page": "val.prob",
      "title": "Validate Predicted Probabilities",
      "concept": [
        "model validation",
        "predictive accuracy",
        "logistic regression model",
        "sampling"
      ],
      "topics": [
        "plot.val.prob",
        "print.val.prob",
        "val.prob"
      ]
    },
    {
      "page": "val.surv",
      "title": "Validate Predicted Probabilities Against Observed Survival Times",
      "concept": [
        "model validation",
        "predictive accuracy"
      ],
      "topics": [
        "plot.val.surv",
        "plot.val.survh",
        "print.val.survh",
        "val.surv"
      ]
    },
    {
      "page": "validate",
      "title": "Resampling Validation of a Fitted Model's Indexes of Fit",
      "concept": [
        "model validation",
        "predictive accuracy",
        "bootstrap"
      ],
      "topics": [
        "html.validate",
        "latex.validate",
        "print.validate",
        "validate"
      ]
    },
    {
      "page": "validate.cph",
      "title": "Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit",
      "concept": [
        "model validation",
        "predictive accuracy",
        "bootstrap"
      ],
      "topics": [
        "dxy.cens",
        "validate.cph",
        "validate.psm"
      ]
    },
    {
      "page": "validate.lrm",
      "title": "Resampling Validation of a Logistic or Ordinal Regression Model",
      "concept": [
        "logistic regression model",
        "model validation",
        "predictive accuracy",
        "bootstrap"
      ],
      "topics": [
        "validate.lrm",
        "validate.orm"
      ]
    },
    {
      "page": "validate.ols",
      "title": "Validation of an Ordinary Linear Model",
      "concept": [
        "model validation",
        "bootstrap",
        "predictive accuracy"
      ],
      "topics": [
        "validate.ols"
      ]
    },
    {
      "page": "validate.rpart",
      "title": "Dxy and Mean Squared Error by Cross-validating a Tree Sequence",
      "concept": [
        "model validation",
        "predictive accuracy"
      ],
      "topics": [
        "plot.validate.rpart",
        "print.validate.rpart",
        "validate.rpart"
      ]
    },
    {
      "page": "validate.Rq",
      "title": "Validation of a Quantile Regression Model",
      "concept": [
        "model validation",
        "bootstrap",
        "predictive accuracy"
      ],
      "topics": [
        "validate.Rq"
      ]
    },
    {
      "page": "vif",
      "title": "Variance Inflation Factors",
      "topics": [
        "vif"
      ]
    },
    {
      "page": "which.influence",
      "title": "Which Observations are Influential",
      "concept": [
        "logistic regression model"
      ],
      "topics": [
        "show.influence",
        "which.influence"
      ]
    },
    {
      "page": "Xcontrast",
      "title": "Xcontrast",
      "topics": [
        "Xcontrast"
      ]
    }
  ],
  "_readme": "https://github.com/harrelfe/rms/raw/HEAD/README.md",
  "_rundeps": [
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  "_sysdeps": [
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