Learn R Programming
⚠️There's a newer version (1.3.3.1) of this package.Take me there.

mcr (version 1.2.1)

Method Comparison Regression

Description

This package provides 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.

Copy Link

Version

Install

install.packages('mcr')

Monthly Downloads

3,078

Version

1.2.1

License

GPL (>= 3)

Maintainer

Fabian Model

Last Published

February 12th, 2014

Functions in mcr (1.2.1)

MCResult.plotDifference

Bland-Altman Plot
MCResult.calcBias

Systematical Bias Between Reference Method and Test Method
MCResult.getErrorRatio

Get Error Ratio
mc.calcAngleMat.R

Calculate Matrix of All Pair-wise Slope Angles
MCResult.getFitted

Get Fitted Values.
mc.make.CIframe

Returns Results of Calculations in Matrix Form
mc.analytical.ci

Analytical Confidence Interval
newMCResultBCa

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

Calculate Weighted Deming Regression
MCResultJackknife.initialize

Initialize Method for 'MCResultJackknife' Objects.
MCResult-class

Class "MCResult"
MCResult.getWeights

Get Weights of Data Points
MCResult.plotResiduals

Plot Residuals of an MCResult Object
MCResultBCa.calcResponse

Caluculate Response
MCResultBCa.initialize

Initialize Method for 'MCResultBCa' Objects.
MCResultAnalytical.printSummary

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

Get-Method for Jackknife-Intercept Value.
creatinine

Comparison of blood and serum creatinine measurement
MCResultAnalytical.initialize

Initialize Method for 'MCResultAnalytical' Objects.
mc.linreg

Calculate ordinary linear Regression and Estimate Standard Errors
MCResultJackknife.getJackknifeStatistics

Jackknife Statistics
MCResultResampling.bootstrapSummary

Compute Bootstrap-Summary for 'MCResultResampling' Objects.
mcr-package

Method Comparison Regression
mc.calcLinnetCI

Jackknife Confidence Interval
MCResultJackknife.getRJIF

Relative Jackknife Influence Function
compareFit

Graphical Comparison of Regression Parameters and Associated Confidence Intervals
mc.paba

Passing-Bablok Regression
calcDiff

Calculate difference between two numeric vectors that gives exactly zero for very small relative differences.
MCResultResampling-class

Class "MCResultResampling"
mc.wlinreg

Calculate Weighted Ordinary Linear Regression and Estimate Standard Errors
newMCResultAnalytical

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

MCResult Object Initialization
MCResultBCa.plotBootstrapT

Plot distriblution of bootstrap pivot T
mcreg

Comparison of Two Measurement Methods Using Regression Analysis
newMCResult

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

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

Compute Resampling T-statistic.
mc.paba.LargeData

Passing-Bablok Regression for Large Datasets
MCResult.getResiduals

Get Regression Residuals
MCResult.calcResponse

Calculate Response with Confidence Interval.
MCResultResampling.printSummary

Print Regression-Analysis Summary for Objects of class 'MCResultResampling'.
mc.calc.quant

Quantile Calculation for BCa
MCResultResampling.plotBootstrapT

Plot distriblution of bootstrap pivot T
mc.calc.tboot

Bootstrap-t Method for Calculation of Resampling Confidence Intervals
MCResultBCa.printSummary

Print Regression-Analysis Summary for Objects of class 'MCResultBCa'.
MCResult.getData

Get Data
mc.calc.Student

Student Method for Calculation of Resampling Confidence Intervals
MCResultAnalytical-class

Class "MCResultAnalytical"
MCResultBCa.plotBootstrapCoefficients

Plot distriblution of bootstrap coefficients
MCResult.getCoefficients

Get Regression Coefficients
includeLegend

Include Legend
MCResultBCa-class

Class "MCResultBCa"
MCResult.plotBias

Plot Estimated Systematical Bias with Confidence Bounds
MCResult.printSummary

Print Summary of a Regression Analysis
MCResultJackknife.getJackknifeSlope

Get-Method for Jackknife-Slope Value.
mc.calc.bca

Bias Corrected and Accelerated Resampling Confidence Interval
MCResultBCa.bootstrapSummary

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

Caluculate Response
MCResult.calcCUSUM

Calculate CUSUM Statistics According to Passing & Bablok (1983)
newMCResultJackknife

MCResultJackknife Object Constructor with Matrix in Wide Format as Input
MCResultAnalytical.calcResponse

Caluculate Response
MCResultJackknife-class

Class "MCResultJackknife"
mc.bootstrap

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

Quantile Method for Calculation of Resampling Confidence Intervals
MCResult.getRegmethod

Get Regression Method
MCResult.plot

Scatter Plot Method X vs. Method Y
MCResultJackknife.calcResponse

Caluculate Response
mc.deming

Calculate Unweighted Deming Regression and Estimate Standard Errors
MCResultResampling.initialize

Initialize Method for 'MCResultAnalytical' Objects.
newMCResultResampling

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

Plot distriblution of bootstrap coefficients
MCResultJackknife.printSummary

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

Plotting the Relative Jackknife Influence Function