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OptimalCutpoints  

Computing Optimal Cutpoints in Diagnostic Tests
View on CRAN: Click here


Download and install OptimalCutpoints package within the R console
Install from CRAN:
install.packages("OptimalCutpoints")

Install from Github:
library("remotes")
install_github("cran/OptimalCutpoints")

Install by package version:
library("remotes")
install_version("OptimalCutpoints", "1.1-5")



Attach the package and use:
library("OptimalCutpoints")
Maintained by
Monica Lopez Raton
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-05-25
Latest Update: 2021-10-07
Description:
Computes optimal cutpoints for diagnostic tests or continuous markers. Various approaches for selecting optimal cutoffs have been implemented, including methods based on cost-benefit analysis and diagnostic test accuracy measures (Sensitivity/Specificity, Predictive Values and Diagnostic Likelihood Ratios). Numerical and graphical output for all methods is easily obtained.
How to cite:
Monica Lopez Raton (2012). OptimalCutpoints: Computing Optimal Cutpoints in Diagnostic Tests. R package version 1.1-5, https://cran.r-project.org/web/packages/OptimalCutpoints. Accessed 28 Jan. 2025.
Previous versions and publish date:
1.0 (2012-05-25 13:01), 1.1-1 (2014-02-25 16:44), 1.1-2 (2014-05-13 21:46), 1.1-3 (2014-11-02 12:38), 1.1-4 (2019-04-01 19:40), 1.1 (2013-09-20 14:57)
Other packages that cited OptimalCutpoints R package
View OptimalCutpoints citation profile
Other R packages that OptimalCutpoints depends, imports, suggests or enhances
Complete documentation for OptimalCutpoints
Functions, R codes and Examples using the OptimalCutpoints R package
Some associated functions: OptimalCutpoints-package . control.cutpoints . elas . optimal.cutpoints . plot.optimal.cutpoints . print.optimal.cutpoints . summary.optimal.cutpoints . 
Some associated R codes: calculate.accuracy.measures.R . calculate.empirical.AUC.R . calculate.sample.prev.R . ci.AgrestiCoull.R . ci.GartNam.R . ci.NotTransformed.R . ci.RubinSchenker.R . ci.exact.R . ci.quadratic.R . ci.transformed.R . ci.wald.R . confidence.intervals.R . control.cutpoints.R . function.CB.R . function.MCT.R . function.MaxDOR.R . function.MaxEfficiency.R . function.MaxKappa.R . function.MaxNPVPPV.R . function.MaxProdNPVPPV.R . function.MaxProdSpSe.R . function.MaxSe.R . function.MaxSp.R . function.MaxSpSe.R . function.MaxSumNPVPPV.R . function.MeanPrev.R . function.MinPvalue.R . function.MinValueNPV.R . function.MinValueNPVPPV.R . function.MinValuePPV.R . function.MinValueSe.R . function.MinValueSp.R . function.MinValueSpSe.R . function.Minimax.R . function.NPVEqualPPV.R . function.ObservedPrev.R . function.PROC01.R . function.PrevalenceMatching.R . function.ROC01.R . function.SpEqualSe.R . function.ValueDLR.Negative.R . function.ValueDLR.Positive.R . function.ValueNPV.R . function.ValuePPV.R . function.ValueSe.R . function.ValueSp.R . function.Youden.R . obtain.optimal.measures.R . optimal.cutpoints.R . optimal.cutpoints.default.R . optimal.cutpoints.formula.R . plot.optimal.cutpoints.R . print.optimal.cutpoints.R . print.summary.optimal.cutpoints.R . summary.optimal.cutpoints.R . validate.prevalence.R .  Full OptimalCutpoints package functions and examples
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