Package: optimalThreshold 1.0
optimalThreshold: Bayesian Methods for Optimal Threshold Estimation
Functions to estimate the optimal threshold of diagnostic markers or treatment selection markers. The optimal threshold is the marker value that maximizes the utility of the marker based-strategy (for diagnostic or treatment selection) in a given population. The utility function depends on the type of marker (diagnostic or treatment selection), but always takes into account the preferences of the patients or the physician in the decision process. For estimating the optimal threshold, ones must specify the distributions of the marker in different groups (defined according to the type of marker, diagnostic or treatment selection) and provides data to estimate the parameters of these distributions. Ones must also provide some features of the target populations (disease prevalence or treatment efficacies) as well as the preferences of patients or physicians. The functions rely on Bayesian inference which helps producing several indicators derived from the optimal threshold. See Blangero, Y, Rabilloud, M, Ecochard, R, and Subtil, F (2019) <doi:10.1177/0962280218821394> for the original article that describes the estimation method for treatment selection markers and Subtil, F, and Rabilloud, M (2019) <doi:10.1002/bimj.200900242> for diagnostic markers.
Authors:
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optimalThreshold.pdf |optimalThreshold.html✨
optimalThreshold/json (API)
# Install 'optimalThreshold' in R: |
install.packages('optimalThreshold', repos = c('https://yblan.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:66de5c78d7. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 15 2024 |
R-4.5-win | OK | Nov 15 2024 |
R-4.5-linux | OK | Nov 15 2024 |
R-4.4-win | OK | Nov 15 2024 |
R-4.4-mac | OK | Nov 15 2024 |
R-4.3-win | OK | Nov 15 2024 |
R-4.3-mac | OK | Nov 15 2024 |
Exports:cdfcredibleIntervalsdecisionCurvedensCurvesdiagThreshestimatesfitgradienthessianplotriskCurvessamplePosteriorDistshowsummarytrtSelThresh
Readme and manuals
Help Manual
Help page | Topics |
---|---|
An S4 union class to represent allowed dist object. | allowedDist allowedDist-class |
An S4 union class to represent allowed fitDist objects. | allowedFitDist allowedFitDist-class |
Cumulative distribution function of a specified distribution | cdf cdf,compoundEvtInnovDist-method cdf,compoundEvtRefDist-method cdf,compoundNoEvtInnovDist-method cdf,compoundNoEvtRefDist-method cdf,gammaDist-method cdf,logisticDist-method cdf,logNormalDist-method cdf,normalDist-method cdf,studentDist-method cdf.compoundEvtInnovDist cdf.compoundEvtRefDist cdf.compoundNoEvtInnovDist cdf.compoundNoEvtRefDist cdf.gammaDist cdf.logisticDist cdf.logNormalDist cdf.normalDist cdf.studentDist |
An S4 class to represent a compound distribution. | compoundEvtInnovDist compoundEvtInnovDist-class |
An S4 class to represent a compound distribution. | compoundEvtRefDist compoundEvtRefDist-class |
An S4 class to represent a compound distribution. | compoundNoEvtInnovDist compoundNoEvtInnovDist-class |
An S4 class to represent a compound distribution. | compoundNoEvtRefDist compoundNoEvtRefDist-class |
Credible intervals estimation | credibleIntervals credibleIntervals,diagOptThresh-method credibleIntervals,trtSelOptThresh-method credibleIntervals.diagOptThresh credibleIntervals.trtSelOptThresh |
Decision curve plot | decisionCurve decisionCurve,diagOptThresh-method decisionCurve,trtSelOptThresh-method decisionCurve.diagOptThresh decisionCurve.trtSelOptThresh |
Density curves plot | densCurves |
An S4 class to describe the optimal threshold of a diagnostic marker. | diagOptThresh diagOptThresh-class |
An S4 class to sum up the results from the decisionCurve methods. | diagRelUtility diagRelUtility-class |
Estimation of the optimal threshold of a diagnostic marker | diagThresh |
Indicator estimates | estimates estimates,diagOptThresh-method estimates,trtSelOptThresh-method estimates.diagOptThresh estimates.trtSelOptThresh |
Specify which distribution to fit on the marker values | fit |
An S4 class to fit a gamma distribution on a vector of marker values. | fitGammaDist fitGammaDist-class |
An S4 class to fit a logistic distribution on a vector of marker values. | fitLogisticDist fitLogisticDist-class |
An S4 class to fit a log-normal distribution on a vector of marker values. | fitLogNormalDist fitLogNormalDist-class |
An S4 class to fit a normal distribution on a vector of marker values. | fitNormalDist fitNormalDist-class |
An S4 class to fit a Student distribution on a vector of marker values. | fitStudentDist fitStudentDist-class |
An S4 class to fit a user-defined distribution on a vector of marker values. | fitUserDefinedDist fitUserDefinedDist-class |
An S4 class to represent a gamma distribution. | gammaDist gammaDist-class |
Probability density function of a specified distribution | gradient gradient,compoundEvtInnovDist-method gradient,compoundEvtRefDist-method gradient,compoundNoEvtInnovDist-method gradient,compoundNoEvtRefDist-method gradient,gammaDist-method gradient,logisticDist-method gradient,logNormalDist-method gradient,normalDist-method gradient,studentDist-method gradient.compoundEvtInnovDist gradient.compoundEvtRefDist gradient.compoundNoEvtInnovDist gradient.compoundNoEvtRefDist gradient.gammaDist gradient.logisticDist gradient.logNormalDist gradient.normalDist gradient.studentDist |
Second derivative of the cumulative distribution function of a specified distribution | hessian hessian,compoundEvtInnovDist-method hessian,compoundEvtRefDist-method hessian,compoundNoEvtInnovDist-method hessian,compoundNoEvtRefDist-method hessian,gammaDist-method hessian,logisticDist-method hessian,logNormalDist-method hessian,normalDist-method hessian,studentDist-method hessian.compoundEvtInnovDist hessian.compoundEvtRefDist hessian.compoundNoEvtInnovDist hessian.compoundNoEvtRefDist hessian.gammaDist hessian.logisticDist hessian.logNormalDist hessian.normalDist hessian.studentDist |
An S4 class to represent a logistic distribution. | logisticDist logisticDist-class |
An S4 class to represent a log-normal distribution. | logNormalDist logNormalDist-class |
An S4 union class to merge mcmc.list and NULL types of object. | mcmc.listOrNull mcmc.listOrNull-class |
An S4 class to represent a normal distribution. | normalDist normalDist-class |
Plot method | plot,diagOptThresh-method plot,trtSelOptThresh-method plot-methods plot.diagOptThresh plot.trtSelOptThresh |
Plot the decision curves of a diagnostic marker | plot,diagRelUtility-method plot.diagRelUtility |
Plot the decision curves of a treatment selection marker | plot,trtSelRelUtility-method plot.trtSelRelUtility |
Marker-by-treatment predictiveness curves plot | riskCurves |
Sample in the posterior distribution of the parameters of a given theoretical distribution. | samplePosteriorDist samplePosteriorDist,fitGammaDist-method samplePosteriorDist,fitLogisticDist-method samplePosteriorDist,fitLogNormalDist-method samplePosteriorDist,fitNormalDist-method samplePosteriorDist,fitStudentDist-method samplePosteriorDist.fitGammaDist samplePosteriorDist.fitLogisticDist samplePosteriorDist.fitLogNormalDist samplePosteriorDist.fitNormalDist samplePosteriorDist.fitStudentDist |
Show method | show,diagOptThresh-method show,trtSelOptThresh-method show-methods show.diagOptThresh show.trtSelOptThresh |
An S4 class to represent a scaled Student distribution. | studentDist studentDist-class |
An S4 method that summarizes the results of a 'trtSelOpthThresh' or a 'diagOpthThresh' object. | summary,diagOptThresh-method summary,trtSelOptThresh-method summary-methods summary.diagOptThresh summary.trtSelOptThresh |
An S4 class to describe the optimal threshold of a treatment selection marker. | trtSelOptThresh trtSelOptThresh-class |
An S4 class to the results from the decisionCurve methods. | trtSelRelUtility trtSelRelUtility-class |
Estimation of the optimal threshold of a treatment selection marker | trtSelThresh |
An S4 class to represent an 'undefined' distribution. | undefined undefined-class |