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mcr (version 1.2.2)

Method Comparison Regression

Description

Regression methods to quantify the relation between two measurement methods. In particular it addresses regression problems with errors in both variables and without repeated measurements. The package provides implementations of Deming regression, weighted Deming regression, and Passing-Bablok regression following the CLSI EP09-A3 recommendations for analytical method comparison and bias estimation using patient samples.

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Version

Install

install.packages('mcr')

Monthly Downloads

2,277

Version

1.2.2

License

GPL (>= 3)

Maintainer

Sergej Potapov

Last Published

April 23rd, 2021

Functions in mcr (1.2.2)

MCResult.getResiduals

Get Regression Residuals
MCResult.plotBias

Plot Estimated Systematical Bias with Confidence Bounds
MCResult.getRegmethod

Get Regression Method
MCResult.plot

Scatter Plot Method X vs. Method Y
MCResult.getFitted

Get Fitted Values.
MCResult.initialize

MCResult Object Initialization
MCResultAnalytical.printSummary

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

Get Weights of Data Points
MCResult.getErrorRatio

Get Error Ratio
MCResult.calcResponse

Calculate Response with Confidence Interval.
MCResultBCa-class

Class "MCResultBCa"
MCResultResampling.bootstrapSummary

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

Plot distriblution of bootstrap pivot T
MCResult.calcBias

Systematical Bias Between Reference Method and Test Method
MCResult-class

Class "MCResult"
MCResultJackknife-class

Class "MCResultJackknife"
mc.calc.Student

Student Method for Calculation of Resampling Confidence Intervals
MCResultResampling.initialize

Initialize Method for 'MCResultAnalytical' Objects.
mc.calc.bca

Bias Corrected and Accelerated Resampling Confidence Interval
MCResultBCa.printSummary

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

Plot distriblution of bootstrap coefficients
MCResultJackknife.getJackknifeIntercept

Get-Method for Jackknife-Intercept Value.
MCResult.printSummary

Print Summary of a Regression Analysis
MCResultAnalytical-class

Class "MCResultAnalytical"
newMCResult

MCResult Object Constructor with Matrix in Wide Format as Input
MCResult.plotDifference

Bland-Altman Plot
newMCResultAnalytical

MCResultAnalytical object constructor with matrix in wide format as input.
MCResult.getCoefficients

Get Regression Coefficients
newMCResultResampling

MCResultResampling object constructor with matrix in wide format as input.
calcDiff

Calculate difference between two numeric vectors that gives exactly zero for very small relative differences.
MCResultJackknife.printSummary

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

Caluculate Response
compareFit

Graphical Comparison of Regression Parameters and Associated Confidence Intervals
MCResultResampling-class

Class "MCResultResampling"
MCResult.plotResiduals

Plot Residuals of an MCResult Object
MCResultBCa.bootstrapSummary

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

Caluculate Response
mc.calcLinnetCI

Jackknife Confidence Interval
mc.calcAngleMat

Calculate Matrix of All Pair-wise Slope Angles
MCResultBCa.calcResponse

Caluculate Response
MCResultJackknife.plotwithRJIF

Plotting the Relative Jackknife Influence Function
mc.calcAngleMat.R

Calculate Matrix of All Pair-wise Slope Angles
newMCResultBCa

MCResultBCa object constructor with matrix in wide format as input.
mc.calc.tboot

Bootstrap-t Method for Calculation of Resampling Confidence Intervals
MCResultJackknife.initialize

Initialize Method for 'MCResultJackknife' Objects.
newMCResultJackknife

MCResultJackknife Object Constructor with Matrix in Wide Format as Input
MCResultJackknife.getJackknifeSlope

Get-Method for Jackknife-Slope Value.
creatinine

Comparison of blood and serum creatinine measurement
mc.analytical.ci

Analytical Confidence Interval
includeLegend

Include Legend
mc.paba

Passing-Bablok Regression
mc.deming

Calculate Unweighted Deming Regression and Estimate Standard Errors
mc.paba.LargeData

Passing-Bablok Regression for Large Datasets
mc.calcTstar

Compute Resampling T-statistic.
mc.calc.quant

Quantile Calculation for BCa
mc.bootstrap

Resampling estimation of regression parameters and standard errors.
mc.calc.quantile

Quantile Method for Calculation of Resampling Confidence Intervals
mc.wdemingConstCV

Calculate Weighted Deming Regression
mc.wlinreg

Calculate Weighted Ordinary Linear Regression and Estimate Standard Errors
mc.linreg

Calculate ordinary linear Regression and Estimate Standard Errors
MCResult.getData

Get Data
MCResultAnalytical.initialize

Initialize Method for 'MCResultAnalytical' Objects.
MCResultAnalytical.calcResponse

Caluculate Response
MCResultBCa.initialize

Initialize Method for 'MCResultBCa' Objects.
MCResultBCa.plotBootstrapCoefficients

Plot distriblution of bootstrap coefficients
mc.make.CIframe

Returns Results of Calculations in Matrix Form
mcreg

Comparison of Two Measurement Methods Using Regression Analysis
MCResultJackknife.getRJIF

Relative Jackknife Influence Function
MCResultResampling.printSummary

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

Jackknife Statistics
MCResultResampling.plotBootstrapT

Plot distriblution of bootstrap pivot T
mcr-package

Method Comparison Regression
MCResult.calcCUSUM

Calculate CUSUM Statistics According to Passing & Bablok (1983)