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mcr (version 1.3.3.1)

Method Comparison Regression

Description

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, ) 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, ) and J. Raymaekers and F. Dufey (2022, ). A comprehensive overview over the implemented methods and references can be found in the manual pages "mcr-package" and "mcreg".

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Version

Install

install.packages('mcr')

Monthly Downloads

3,078

Version

1.3.3.1

License

GPL (>= 3)

Maintainer

Last Published

September 23rd, 2024

Functions in mcr (1.3.3.1)

MCResult.plot

Scatter Plot Method X vs. Method Y
MCResult.getWeights

Get Weights of Data Points
MCResult.plotResiduals

Plot Residuals of an MCResult Object
MCResult.plotDifference

Bland-Altman Plot
MCResult.initialize

MCResult Object Initialization
MCResultAnalytical.printSummary

Print Regression-Analysis Summary for Objects of class 'MCResultAnalytical'.
MCResult.plotBias

Plot Estimated Systematical Bias with Confidence Bounds
MCResult.printSummary

Print Summary of a Regression Analysis
MCResultAnalytical-class

Class "MCResultAnalytical"
MCResult.calcBias

Systematical Bias Between Reference Method and Test Method
MCResultBCa-class

Class "MCResultBCa"
MCResultBCa.plotBootstrapT

Plot distriblution of bootstrap pivot T
MCResultAnalytical.calcResponse

Caluculate Response
MCResultAnalytical.initialize

Initialize Method for 'MCResultAnalytical' Objects.
MCResultJackknife.calcResponse

Caluculate Response
MCResultJackknife-class

Class "MCResultJackknife"
MCResultBCa.calcResponse

Caluculate Response
MCResultBCa.bootstrapSummary

Compute Bootstrap-Summary for 'MCResultBCa' Objects.
MCResultResampling.calcResponse

Caluculate Response
MCResultBCa.printSummary

Print Regression-Analysis Summary for Objects of class 'MCResultBCa'.
MCResultJackknife.initialize

Initialize Method for 'MCResultJackknife' Objects.
MCResultResampling.bootstrapSummary

Compute Bootstrap-Summary for 'MCResultResampling' Objects.
MCResultJackknife.plotwithRJIF

Plotting the Relative Jackknife Influence Function
MCResultJackknife.getJackknifeIntercept

Get-Method for Jackknife-Intercept Value.
MCResultJackknife.getJackknifeSlope

Get-Method for Jackknife-Slope Value.
MCResultResampling.printSummary

Print Regression-Analysis Summary for Objects of class 'MCResultResampling'.
MCResultResampling.plotBootstrapT

Plot distriblution of bootstrap pivot T
mc.PBequi

Equivariant Passing-Bablok Regression
MCResultBCa.initialize

Initialize Method for 'MCResultBCa' Objects.
mc.calcLinnetCI

Jackknife Confidence Interval
MCResultJackknife.printSummary

Print Regression-Analysis Summary for Objects of class 'MCResultJackknife'.
MCResultResampling-class

Class "MCResultResampling"
includeLegend

Include Legend
mc.calcTstar

Compute Resampling T-statistic.
MCResultBCa.plotBootstrapCoefficients

Plot distriblution of bootstrap coefficients
creatinine

Comparison of blood and serum creatinine measurement
mc.calcAngleMat.R

Calculate Matrix of All Pair-wise Slope Angles
MCResultJackknife.getJackknifeStatistics

Jackknife Statistics
mc.deming

Calculate Unweighted Deming Regression and Estimate Standard Errors
mc.calcAngleMat

Calculate Matrix of All Pair-wise Slope Angles
mc.paba

Passing-Bablok Regression
MCResultJackknife.getRJIF

Relative Jackknife Influence Function
calcDiff

Calculate difference between two numeric vectors that gives exactly zero for very small relative differences.
mc.analytical.ci

Analytical Confidence Interval
mcreg

Comparison of Two Measurement Methods Using Regression Analysis
newMCResult

MCResult Object Constructor with Matrix in Wide Format as Input
mc.wdemingConstCV

Calculate Weighted Deming Regression
mc.bootstrap

Resampling estimation of regression parameters and standard errors.
compareFit

Graphical Comparison of Regression Parameters and Associated Confidence Intervals
mc.calc.Student

Student Method for Calculation of Resampling Confidence Intervals
newMCResultJackknife

MCResultJackknife Object Constructor with Matrix in Wide Format as Input
MCResultResampling.initialize

Initialize Method for 'MCResultAnalytical' Objects.
MCResultResampling.plotBootstrapCoefficients

Plot distriblution of bootstrap coefficients
mc.calc.quant

Quantile Calculation for BCa
mc.calc.bca

Bias Corrected and Accelerated Resampling Confidence Interval
mc.calc.quantile

Quantile Method for Calculation of Resampling Confidence Intervals
newMCResultResampling

MCResultResampling object constructor with matrix in wide format as input.
mc.linreg

Calculate ordinary linear Regression and Estimate Standard Errors
mc.calc.tboot

Bootstrap-t Method for Calculation of Resampling Confidence Intervals
mc.wlinreg

Calculate Weighted Ordinary Linear Regression and Estimate Standard Errors
mcr-package

Method Comparison Regression
mc.make.CIframe

Returns Results of Calculations in Matrix Form
mc.paba.LargeData

Passing-Bablok Regression for Large Datasets
newMCResultAnalytical

MCResultAnalytical object constructor with matrix in wide format as input.
newMCResultBCa

MCResultBCa object constructor with matrix in wide format as input.
MCResult.calcCUSUM

Calculate CUSUM Statistics According to Passing & Bablok (1983)
MCResult.calcResponse

Calculate Response with Confidence Interval.
MCResult.getErrorRatio

Get Error Ratio
MCResult.getCoefficients

Get Regression Coefficients
MCResult-class

Class "MCResult"
MCResult.getRegmethod

Get Regression Method
MCResult.getData

Get Data
MCResult.getFitted

Get Fitted Values.
MCResult.getResiduals

Get Regression Residuals