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A B C D E F G H I L M N O P Q R S T U V W
| %ia% | Design Special Transformation Functions |
| anova.Design | Analysis of Variance (Wald and F Statistics) |
| asis | Design Special Transformation Functions |
| bj | Buckley-James Multiple Regression Model |
| bjplot | Buckley-James Multiple Regression Model |
| bootcov | Bootstrap Covariance and Distribution for Regression Coefficients |
| bootplot | Bootstrap Covariance and Distribution for Regression Coefficients |
| calibrate | Resampling Model Calibration |
| catg | Design Special Transformation Functions |
| confplot | Bootstrap Covariance and Distribution for Regression Coefficients |
| contrast | General Contrasts of Regression Coefficients |
| cph | Cox Proportional Hazards Model and Extensions |
| cr.setup | Continuation Ratio Ordinal Logistic Setup |
| datadensity | Plot Effects of Variables |
| datadensity.plot.Design | Plot Effects of Variables |
| datadist | Distribution Summaries for Predictor Variables |
| Design | Design Methods and Generic Functions |
| Design.Misc | Miscellaneous Design Attributes and Utility Functions |
| Design.Overview | Overview of Design Library |
| Design.trans | Design Special Transformation Functions |
| DesignFit | Miscellaneous Design Attributes and Utility Functions |
| effective.df | Trace AIC and BIC vs. Penalty |
| fastbw | Fast Backward Variable Selection |
| Function.cph | Compose an S Function to Compute X beta from a Fit |
| Function.Design | Compose an S Function to Compute X beta from a Fit |
| gendata | Generate Data Frame with Predictor Combinations |
| Getlim | Miscellaneous Design Attributes and Utility Functions |
| Getlimi | Miscellaneous Design Attributes and Utility Functions |
| glmD | Design Version of glm |
| glsD | Fit Linear Model Using Generalized Least Squares |
| groupkm | Kaplan-Meier Estimates vs. a Continuous Variable |
| Hazard | Parametric Survival Model |
| hazard.ratio.plot | Hazard Ratio Plot |
| histdensity | Bootstrap Covariance and Distribution for Regression Coefficients |
| ie.setup | Intervening Event Setup |
| interactions.containing | Miscellaneous Design Attributes and Utility Functions |
| latex | LaTeX Representation of a Fitted Model |
| latex.anova.Design | Analysis of Variance (Wald and F Statistics) |
| latex.bj | LaTeX Representation of a Fitted Model |
| latex.cph | LaTeX Representation of a Fitted Cox Model |
| latex.Design | LaTeX Representation of a Fitted Model |
| latex.glmD | LaTeX Representation of a Fitted Model |
| latex.glsD | LaTeX Representation of a Fitted Model |
| latex.lrm | LaTeX Representation of a Fitted Cox Model |
| latex.ols | LaTeX Representation of a Fitted Cox Model |
| latex.pphsm | LaTeX Representation of a Fitted Cox Model |
| latex.psm | LaTeX Representation of a Fitted Cox Model |
| latex.summary.Design | Summary of Effects in Model |
| latexDesign | LaTeX Representation of a Fitted Model |
| Legend | Plot Effects of Variables |
| legend.nomabbrev | Draw a Nomogram |
| Legend.plot.Design | Plot Effects of Variables |
| lines.perimeter | Plot Effects of Variables |
| lines.residuals.psm.censored.normalized | Parametric Survival Model |
| lrm | Logistic Regression Model |
| lrm.fit | Logistic Model Fitter |
| lrtest | Miscellaneous Design Attributes and Utility Functions |
| lsp | Design Special Transformation Functions |
| matinv | Total and Partial Matrix Inversion using Gauss-Jordan Sweep Operator |
| matrx | Design Special Transformation Functions |
| Mean.cph | Cox Proportional Hazards Model and Extensions |
| Mean.lrm | Predicted Values for Binary and Ordinal Logistic Models |
| Mean.psm | Parametric Survival Model |
| Newlabels | Miscellaneous Design Attributes and Utility Functions |
| Newlevels | Miscellaneous Design Attributes and Utility Functions |
| nomogram | Draw a Nomogram |
| num.intercepts | Miscellaneous Design Attributes and Utility Functions |
| ols | Linear Model Estimation Using Ordinary Least Squares |
| oos.loglik | Miscellaneous Design Attributes and Utility Functions |
| Overview | Overview of Design Library |
| param.order | Miscellaneous Design Attributes and Utility Functions |
| pbind | Imputation of Repeated Measures |
| Penalty.matrix | Miscellaneous Design Attributes and Utility Functions |
| Penalty.setup | Miscellaneous Design Attributes and Utility Functions |
| pentrace | Trace AIC and BIC vs. Penalty |
| perimeter | Plot Effects of Variables |
| plot.anova.Design | Analysis of Variance (Wald and F Statistics) |
| plot.calibrate | Resampling Model Calibration |
| plot.Design | Plot Effects of Variables |
| plot.lrm.partial | Residuals from a Logistic Regression Model Fit |
| plot.pentrace | Trace AIC and BIC vs. Penalty |
| plot.sensuc | Sensitivity to Unmeasured Covariables |
| plot.summary.Design | Summary of Effects in Model |
| plot.val.prob | Validate Predicted Probabilities |
| plot.val.surv | Validate Predicted Probabilities |
| plot.validate.tree | Dxy and Mean Squared Error by Cross-validating a Tree Sequence |
| plot.xmean.ordinaly | Plot Mean X vs. Ordinal Y |
| pol | Design Special Transformation Functions |
| pphsm | Parametric Proportional Hazards form of AFT Models |
| predab.resample | Predictive Ability using Resampling |
| predict.bj | Predicted Values from Model Fit |
| predict.cph | Predicted Values from Model Fit |
| predict.Design | Predicted Values from Model Fit |
| predict.glmD | Predicted Values from Model Fit |
| predict.glsD | Predicted Values from Model Fit |
| predict.lrm | Predicted Values for Binary and Ordinal Logistic Models |
| predict.ols | Predicted Values from Model Fit |
| predict.psm | Predicted Values from Model Fit |
| predictDesign | Predicted Values from Model Fit |
| print.anova.Design | Analysis of Variance (Wald and F Statistics) |
| print.bj | Buckley-James Multiple Regression Model |
| print.calibrate | Resampling Model Calibration |
| print.contrast.Design | General Contrasts of Regression Coefficients |
| print.cph | Print cph Results |
| print.cph.fit | Print cph.fit |
| print.datadist | Distribution Summaries for Predictor Variables |
| print.Design | Miscellaneous Design Attributes and Utility Functions |
| print.fastbw | Fast Backward Variable Selection |
| print.glmD | Design Version of glm |
| print.glsD | Fit Linear Model Using Generalized Least Squares |
| print.lrm | Print lrm |
| print.lrtest | Miscellaneous Design Attributes and Utility Functions |
| print.nomogram | Draw a Nomogram |
| print.ols | Print ols |
| print.pentrace | Trace AIC and BIC vs. Penalty |
| print.plot.Design | Plot Effects of Variables |
| print.pphsm | Parametric Proportional Hazards form of AFT Models |
| print.psm | Parametric Survival Model |
| print.specs.Design | Design Specifications for Models |
| print.summary.Design | Summary of Effects in Model |
| print.survest.psm | Parametric Survival Estimates |
| print.val.prob | Validate Predicted Probabilities |
| print.validate.tree | Dxy and Mean Squared Error by Cross-validating a Tree Sequence |
| psm | Parametric Survival Model |
| Quantile.cph | Cox Proportional Hazards Model and Extensions |
| Quantile.psm | Parametric Survival Model |
| rcs | Design Special Transformation Functions |
| related.predictors | Miscellaneous Design Attributes and Utility Functions |
| residuals.bj | Buckley-James Multiple Regression Model |
| residuals.cph | Residuals for a cph Fit |
| residuals.Design | Miscellaneous Design Attributes and Utility Functions |
| residuals.lrm | Residuals from a Logistic Regression Model Fit |
| residuals.ols | Residuals for ols |
| residuals.psm | Parametric Survival Model |
| rm.impute | Imputation of Repeated Measures |
| robcov | Robust Covariance Matrix Estimates |
| sascode | Compose an S Function to Compute X beta from a Fit |
| scored | Design Special Transformation Functions |
| sensuc | Sensitivity to Unmeasured Covariables |
| show.influence | Which Observations are Influential |
| specs | Design Specifications for Models |
| strat | Design Special Transformation Functions |
| summary.Design | Summary of Effects in Model |
| summary.survfit | Design version of survival Package summary.survfit |
| Surv.event | Accessors for survivals Surv object. |
| Surv.strata | Accessors for survivals Surv object. |
| Surv.time | Accessors for survivals Surv object. |
| survest | Cox Survival Estimates |
| survest.psm | Parametric Survival Estimates |
| survfit | Modified Version of survival Package survfit Function |
| survfit.cph | Cox Predicted Survival |
| Survival | Parametric Survival Model |
| Survival.cph | Cox Proportional Hazards Model and Extensions |
| Survival.psm | Parametric Survival Model |
| survplot | Plot Survival Curves and Hazard Functions |
| survplot.residuals.psm.censored.normalized | Parametric Survival Model |
| survplot.survfit | Plot Survival Curves and Hazard Functions |
| text.anova.Design | Analysis of Variance (Wald and F Statistics) |
| univarLR | Miscellaneous Design Attributes and Utility Functions |
| val.prob | Validate Predicted Probabilities |
| val.surv | Validate Predicted Probabilities |
| validate | Resampling Validation of a Fitted Model's Indexes of Fit |
| validate.bj | Buckley-James Multiple Regression Model |
| validate.cph | Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit |
| validate.lrm | Resampling Validation of a Logistic Model |
| validate.ols | Validation of an Ordinary Linear Model |
| validate.psm | Validation of a Fitted Cox or Parametric Survival Model's Indexes of Fit |
| validate.rpart | Dxy and Mean Squared Error by Cross-validating a Tree Sequence |
| validate.tree | Dxy and Mean Squared Error by Cross-validating a Tree Sequence |
| Varcov.cph | Miscellaneous Design Attributes and Utility Functions |
| Varcov.glmD | Miscellaneous Design Attributes and Utility Functions |
| Varcov.glsD | Miscellaneous Design Attributes and Utility Functions |
| Varcov.lrm | Miscellaneous Design Attributes and Utility Functions |
| Varcov.ols | Miscellaneous Design Attributes and Utility Functions |
| Varcov.pphsm | Parametric Proportional Hazards form of AFT Models |
| Varcov.psm | Miscellaneous Design Attributes and Utility Functions |
| vif | Variance Inflation Factors |
| which.influence | Which Observations are Influential |