Package: mcrPioda 1.3.3
mcrPioda: Method Comparison Regression - fork for M- and MM-Deming
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 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 "mcr-package" and "mcreg".
Authors:
mcrPioda_1.3.3.tar.gz
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mcrPioda.pdf |mcrPioda.html✨
mcrPioda/json (API)
# Install 'mcrPioda' in R: |
install.packages('mcrPioda', repos = c('https://piodag.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/piodag/mcrpioda/issues
- creatinine - Comparison of blood and serum creatinine measurement
Last updated 2 months agofrom:e2083d1732. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 22 2024 |
R-4.5-win-x86_64 | NOTE | Oct 23 2024 |
R-4.5-linux-x86_64 | NOTE | Oct 23 2024 |
R-4.4-win-x86_64 | NOTE | Nov 22 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 22 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 22 2024 |
R-4.3-win-x86_64 | NOTE | Nov 22 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 22 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 22 2024 |
Exports:calcBiascalcCUSUMcalcResponsecoefcompareFitgetCoefficientsgetDatagetErrorRatiogetFittedgetRegmethodgetResidualsgetRJIFgetWeightsincludeLegendmcregMCResult.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