Package: mcrPioda 1.3.4

Giorgio Pioda

mcrPioda: Method Comparison Regression - Mcr Fork for M- And MM-Deming Regression

Regression methods to quantify the relation between two measurement methods are provided by this package. In particular it addresses regression problems with errors in both variables and without repeated measurements. It implements the Clinical Laboratory Standard International (CLSI) recommendations (see J. A. Budd et al. (2018, <https://clsi.org/standards/products/method-evaluation/documents/ep09/>) for analytical method comparison and bias estimation using patient samples. Furthermore, algorithms for Theil-Sen and equivariant Passing-Bablok estimators are implemented, see F. Dufey (2020, <doi:10.1515/ijb-2019-0157>) and J. Raymaekers and F. Dufey (2022, <arxiv:2202:08060>). Further the robust M-Deming and MM-Deming (experimental) are available, see G. Pioda (2021, <arxiv:2105:04628>). A comprehensive overview over the implemented methods and references can be found in the manual pages 'mcrPioda-package' and 'mcreg'.

Authors:Giorgio Pioda [aut, cre], Sergej Potapov [aut], Fabian Model [aut], Andre Schuetzenmeister [aut], Ekaterina Manuilova [aut], Florian Dufey [aut], Jakob Raymaekers [aut], Venkatraman E. Seshan [ctb], Roche [cph, fnd]

mcrPioda_1.3.4.tar.gz
mcrPioda_1.3.4.tar.gz(r-4.5-noble)mcrPioda_1.3.4.tar.gz(r-4.4-noble)
mcrPioda_1.3.4.tgz(r-4.4-emscripten)mcrPioda_1.3.4.tgz(r-4.3-emscripten)
mcrPioda.pdf |mcrPioda.html
mcrPioda/json (API)
NEWS

# Install 'mcrPioda' in R:
install.packages('mcrPioda', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • gsl– GNU Scientific Library (GSL)
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • creatinine - Comparison of blood and serum creatinine measurement

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 4 scripts 339 downloads 64 exports 81 dependencies

Last updated 2 months agofrom:409357adfc. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKSep 27 2024
R-4.5-linux-x86_64OKSep 27 2024

Exports:calcBiascalcCUSUMcalcPaBaTiesRatiocalcResponsecoefcompareFitgetCoefficientsgetDatagetErrorRatiogetFittedgetRegmethodgetResidualsgetRJIFgetWeightsincludeLegendmcregMCResult.calcBiasMCResult.calcCUSUMMCResult.calcResponseMCResult.getCoefficientsMCResult.getDataMCResult.getErrorRatioMCResult.getFittedMCResult.getRegmethodMCResult.getResidualsMCResult.getWeightsMCResult.initializeMCResult.plotMCResult.plotBiasMCResult.plotDifferenceMCResult.plotResidualsMCResult.printSummaryMCResultAnalytical.calcResponseMCResultAnalytical.initializeMCResultAnalytical.printSummaryMCResultBCa.bootstrapSummaryMCResultBCa.calcResponseMCResultBCa.initializeMCResultBCa.plotBootstrapCoefficientsMCResultBCa.plotBootstrapTMCResultBCa.plotBoxEllipsesMCResultBCa.printSummaryMCResultJackknife.calcResponseMCResultJackknife.getJackknifeInterceptMCResultJackknife.getJackknifeSlopeMCResultJackknife.getJackknifeStatisticsMCResultJackknife.getRJIFMCResultJackknife.initializeMCResultJackknife.plotwithRJIFMCResultJackknife.printSummaryMCResultResampling.bootstrapSummaryMCResultResampling.calcResponseMCResultResampling.initializeMCResultResampling.plotBootstrapCoefficientsMCResultResampling.plotBootstrapTMCResultResampling.plotBoxEllipsesMCResultResampling.printSummaryplotplotBiasplotDifferenceplotResidualsplotwithRJIFprintSummarysummary

Dependencies:askpassbase64encbslibcachemclicolorspacecpp11crosstalkcurldata.tableDEoptimRdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonlitekernlabknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemixtoolsmunsellmvtnormnlmeopensslpcaPPpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownrobslopesrobustbaserrcovsassscalessegmentedstringistringrsurvivalsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Method Comparison Regression - Mcr Fork for M- and MM-Deming RegressionmcrPioda-package mcrPioda
Calculate difference between two numeric vectors that gives exactly zero for very small relative differences.calcDiff
Graphical Comparison of Regression Parameters and Associated Confidence IntervalscompareFit
Comparison of blood and serum creatinine measurementcreatinine
Include LegendincludeLegend
Analytical Confidence Intervalmc.analytical.ci
Resampling estimation of regression parameters and standard errors.mc.bootstrap
Bias Corrected and Accelerated Resampling Confidence Intervalmc.calc.bca
Quantile Calculation for BCamc.calc.quant
Quantile Method for Calculation of Resampling Confidence Intervalsmc.calc.quantile
Student Method for Calculation of Resampling Confidence Intervalsmc.calc.Student
Bootstrap-t Method for Calculation of Resampling Confidence Intervalsmc.calc.tboot
Calculate Matrix of All Pair-wise Slope Anglesmc.calcAngleMat
Calculate Matrix of All Pair-wise Slope Anglesmc.calcAngleMat.R
Jackknife Confidence Intervalmc.calcLinnetCI
Compute Resampling T-statistic.mc.calcTstar
Calculate Unweighted Deming Regression and Estimate Standard Errorsmc.deming
Calculate ordinary linear Regression and Estimate Standard Errorsmc.linreg
Returns Results of Calculations in Matrix Formmc.make.CIframe
Calculate Weighted Deming Regressionmc.mdemingConstCV
Calculate Weighted Deming Regressionmc.mmdemingConstCV
Calculate MM Deming Regressionmc.mmNgdemingConstCV
Calculate MM Deming Regressionmc.mmPidemingConstCV
Passing-Bablok Regressionmc.paba
Passing-Bablok Regression for Large Datasetsmc.paba.LargeData
Equivariant Passing-Bablok Regressionmc.PBequi
Calculate Weighted Deming Regressionmc.wdemingConstCV
Calculate Weighted Ordinary Linear Regression and Estimate Standard Errorsmc.wlinreg
Comparison of Two Measurement Methods Using Regression Analysismcreg
Class '"MCResult"'calcBias,MCResult-method calcCUSUM,MCResult-method calcPaBaTiesRatio,MCResult-method calcResponse,MCResult-method coef,MCResult-method getCoefficients,MCResult-method getData,MCResult-method getErrorRatio,MCResult-method getFitted,MCResult-method getRegmethod,MCResult-method getResiduals,MCResult-method getWeights,MCResult-method MCResult-class plot,MCResult-method plotBias,MCResult-method plotDifference,MCResult-method plotResiduals,MCResult-method printSummary,MCResult-method summary,MCResult-method
Systematical Bias Between Reference Method and Test MethodcalcBias MCResult.calcBias
Calculate CUSUM Statistics According to Passing & Bablok (1983)calcCUSUM MCResult.calcCUSUM
Calculate PaBa Ties Ratio.calcPaBaTiesRatio MCResult.calcPaBaTiesRatio
Calculate Response with Confidence Interval.calcResponse MCResult.calcResponse
Get Regression Coefficientscoef getCoefficients MCResult.getCoefficients
Get DatagetData MCResult.getData
Get Error RatiogetErrorRatio MCResult.getErrorRatio
Get Fitted Values.getFitted MCResult.getFitted
Get Regression MethodgetRegmethod MCResult.getRegmethod
Get Regression ResidualsgetResiduals MCResult.getResiduals
Get Weights of Data PointsgetWeights MCResult.getWeights
MCResult Object InitializationMCResult.initialize
Scatter Plot Method X vs. Method YMCResult.plot plot plot.mcr
Plot Estimated Systematical Bias with Confidence BoundsMCResult.plotBias plotBias
Bland-Altman PlotMCResult.plotDifference plotDifference
Plot Residuals of an MCResult ObjectMCResult.plotResiduals plotResiduals
Print Summary of a Regression AnalysisMCResult.printSummary printSummary summary
Class '"MCResultAnalytical"'calcResponse,MCResultAnalytical-method MCResultAnalytical-class printSummary,MCResultAnalytical-method summary,MCResultAnalytical-method
Calculate ResponseMCResultAnalytical.calcResponse
Initialize Method for 'MCResultAnalytical' Objects.MCResultAnalytical.initialize
Print Regression-Analysis Summary for Objects of class 'MCResultAnalytical'.MCResultAnalytical.printSummary
Class '"MCResultBCa"'calcResponse,MCResultBCa-method MCResultBCa-class printSummary,MCResultBCa-method summary,MCResultBCa-method
Compute Bootstrap-Summary for 'MCResultBCa' Objects.MCResultBCa.bootstrapSummary
Calculate ResponseMCResultBCa.calcResponse
Initialize Method for 'MCResultBCa' Objects.MCResultBCa.initialize
Plot distribution of bootstrap coefficientsMCResultBCa.plotBootstrapCoefficients
Plot distribution of bootstrap pivot TMCResultBCa.plotBootstrapT
Plot Box Ellipses of bootstrap coefficientsMCResultBCa.plotBoxEllipses
Print Regression-Analysis Summary for Objects of class 'MCResultBCa'.MCResultBCa.printSummary
Class '"MCResultJackknife"'calcResponse,MCResultJackknife-method getRJIF,MCResultJackknife-method MCResultJackknife-class plotwithRJIF,MCResultJackknife-method printSummary,MCResultJackknife-method summary,MCResultJackknife-method
Calculate ResponseMCResultJackknife.calcResponse
Get-Method for Jackknife-Intercept Value.MCResultJackknife.getJackknifeIntercept
Get-Method for Jackknife-Slope Value.MCResultJackknife.getJackknifeSlope
Jackknife StatisticsMCResultJackknife.getJackknifeStatistics
Relative Jackknife Influence FunctiongetRJIF MCResultJackknife.getRJIF
Initialize Method for 'MCResultJackknife' Objects.MCResultJackknife.initialize
Plotting the Relative Jackknife Influence FunctionMCResultJackknife.plotwithRJIF plotwithRJIF
Print Regression-Analysis Summary for Objects of class 'MCResultJackknife'.MCResultJackknife.printSummary
Class '"MCResultResampling"'calcResponse,MCResultResampling-method MCResultResampling-class printSummary,MCResultResampling-method summary,MCResultResampling-method
Compute Bootstrap-Summary for 'MCResultResampling' Objects.MCResultResampling.bootstrapSummary
Calculate ResponseMCResultResampling.calcResponse
Initialize Method for 'MCResultAnalytical' Objects.MCResultResampling.initialize
Plot distribution of bootstrap coefficientsMCResultResampling.plotBootstrapCoefficients
Plot distribution of bootstrap pivot TMCResultResampling.plotBootstrapT
Plot Box Ellipses of bootstrap coefficientsMCResultResampling.plotBoxEllipses
Print Regression-Analysis Summary for Objects of class 'MCResultResampling'.MCResultResampling.printSummary
MCResult Object Constructor with Matrix in Wide Format as InputnewMCResult
MCResultAnalytical object constructor with matrix in wide format as input.newMCResultAnalytical
MCResultBCa object constructor with matrix in wide format as input.newMCResultBCa
MCResultJackknife Object Constructor with Matrix in Wide Format as InputnewMCResultJackknife
MCResultResampling object constructor with matrix in wide format as input.newMCResultResampling