abs_d_ppv_npv | Calculate the absolute difference of positive and negative predictive value |

abs_d_sens_spec | Calculate the absolute difference of sensitivity and specificity |

accuracy | Calculate accuracy |

acc_constrain | Metrics that are constrained by another metric |

add_metric | Add metrics to a cutpointr or roc_cutpointr object |

add_metric.cutpointr | Add metrics to a cutpointr or roc_cutpointr object |

add_metric.multi_cutpointr | Add metrics to a cutpointr or roc_cutpointr object |

add_metric.roc_cutpointr | Add metrics to a cutpointr or roc_cutpointr object |

auc | Calculate AUC from a roc_cutpointr or cutpointr object |

auc.cutpointr | Calculate AUC from a roc_cutpointr or cutpointr object |

auc.roc_cutpointr | Calculate AUC from a roc_cutpointr or cutpointr object |

boot_ci | Calculate bootstrap confidence intervals from a cutpointr object |

boot_test | Test for equivalence of a metric |

cohens_kappa | Calculate Cohen's Kappa |

cutpoint | Extract the cutpoints from a ROC curve generated by cutpointr |

cutpointr | Determine and evaluate optimal cutpoints |

cutpointr.default | Determine and evaluate optimal cutpoints |

cutpointr.numeric | Determine and evaluate optimal cutpoints |

cutpointr_ | The standard evaluation version of cutpointr (deprecated) |

cutpoints | Extract the cutpoints from a ROC curve generated by cutpointr |

cutpoint_knots | Calculate number of knots to use in spline smoothing |

F1_score | Calculate the F1-score |

false_discovery_rate | Calculate the false omission and false discovery rate |

false_omission_rate | Calculate the false omission and false discovery rate |

fn | Extract number true / false positives / negatives |

fnr | Calculate true / false positive / negative rate |

fp | Extract number true / false positives / negatives |

fpr | Calculate true / false positive / negative rate |

Jaccard | Calculate the Jaccard Index |

maximize_boot_metric | Optimize a metric function in binary classification after bootstrapping |

maximize_gam_metric | Optimize a metric function in binary classification after smoothing via generalized additive models |

maximize_loess_metric | Optimize a metric function in binary classification after LOESS smoothing |

maximize_metric | Optimize a metric function in binary classification |

maximize_spline_metric | Optimize a metric function in binary classification after spline smoothing |

metric_constrain | Metrics that are constrained by another metric |

minimize_boot_metric | Optimize a metric function in binary classification after bootstrapping |

minimize_gam_metric | Optimize a metric function in binary classification after smoothing via generalized additive models |

minimize_loess_metric | Optimize a metric function in binary classification after LOESS smoothing |

minimize_metric | Optimize a metric function in binary classification |

minimize_spline_metric | Optimize a metric function in binary classification after spline smoothing |

misclassification_cost | Calculate the misclassification cost |

multi_cutpointr | Calculate optimal cutpoints and further statistics for multiple predictors |

nlr | Calculate the positive or negative likelihood ratio |

npv | Calculate the negative predictive value |

oc_manual | Set a manual cutpoint for use with cutpointr |

oc_mean | Use the sample mean as cutpoint |

oc_median | Use the sample median as cutpoint |

oc_youden_kernel | Determine an optimal cutpoint maximizing the Youden-Index based on kernel smoothed densities |

oc_youden_normal | Determine an optimal cutpoint for the Youden-Index assuming normal distributions |

odds_ratio | Calculate the odds ratio |

plot.cutpointr | Plot cutpointr objects |

plot.multi_cutpointr | Plotting multi_cutpointr objects is currently not supported |

plot.roc_cutpointr | Plot ROC curve from a cutpointr or roc_cutpointr object |

plot_cutpointr | General purpose plotting function for cutpointr or roc_cutpointr objects |

plot_cut_boot | Plot the bootstrapped distribution of optimal cutpoints from a cutpointr object |

plot_metric | Plot a metric over all possible cutoffs from a cutpointr object |

plot_metric_boot | Plot the bootstrapped metric distribution from a cutpointr object |

plot_precision_recall | Precision recall plot from a cutpointr object |

plot_roc | Plot ROC curve from a cutpointr or roc_cutpointr object |

plot_roc.cutpointr | Plot ROC curve from a cutpointr or roc_cutpointr object |

plot_roc.roc_cutpointr | Plot ROC curve from a cutpointr or roc_cutpointr object |

plot_sensitivity_specificity | Sensitivity and specificity plot from a cutpointr object |

plot_x | Plot the distribution of the independent variable per class from a cutpointr object |

plr | Calculate the positive or negative likelihood ratio |

ppv | Calculate the positive predictive value |

precision | Calculate precision |

predict.cutpointr | Predict using a cutpointr object |

print.cutpointr | Print cutpointr objects |

print.multi_cutpointr | Print multi_cutpointr objects |

prod_ppv_npv | Calculate the product of positive and negative predictive value |

prod_sens_spec | Calculate the product of sensitivity and specificity |

prostate_nodal | Nodal involvement and acid phosphatase levels in 53 prostate cancer patients |

p_chisquared | Calculate the p-value of a chi-squared test |

recall | Calculate recall |

risk_ratio | Calculate the risk ratio (relative risk) |

roc | Calculate a ROC curve |

roc01 | Calculate the distance between points on the ROC curve and (0,1) |

sensitivity | Calculate sensitivity |

sens_constrain | Metrics that are constrained by another metric |

specificity | Calculate specificity |

spec_constrain | Metrics that are constrained by another metric |

suicide | Suicide attempts and DSI sum scores of 532 subjects |

sum_ppv_npv | Calculate the sum of positive and negative predictive value |

sum_sens_spec | Calculate the sum of sensitivity and specificity |

tn | Extract number true / false positives / negatives |

tnr | Calculate true / false positive / negative rate |

total_utility | Calculate the total utility |

tp | Extract number true / false positives / negatives |

tpr | Calculate true / false positive / negative rate |

user_span_cutpointr | Calculate bandwidth for LOESS smoothing of metric functions by rule of thumb |

youden | Calculate the Youden-Index |