Type:	Package
Title:	Non-Parametric Concordance Coefficient
Version:	1.0.9
Date:	2024-10-16
Description:	A non-parametric test for multi-observer concordance and differences between concordances in (un)balanced data.
License:	GPL (≥ 3)
Depends:	R (≥ 3.5.0)
Imports:	methods, Matrix (≥ 1.1.5), parallel, stats
Suggests:	MASS
RoxygenNote:	7.3.2
Encoding:	UTF-8
NeedsCompilation:	yes
Packaged:	2024-10-16 13:57:43 UTC; rkuiper
Author:	Rowan Kuiper [cre, aut], Remco Hoogenboezem [aut], Sjoerd Huisman [ctb], Pieter Sonneveld [ths], Mark van Duin [ths]
Maintainer:	Rowan Kuiper <r.kuiper.emc@gmail.com>
Repository:	CRAN
Date/Publication:	2024-10-16 14:10:01 UTC

Extract argument values from a ConcordanceTest object

Description

Extracts argument values from a ConcordanceTest-class object

Usage

## S4 method for signature 'ConcordanceTest'
x$name

Arguments

Value

The value of the requested argument

Examples

matRandom <- matrix(rnorm(3*20),20,3)
testResult <- concordance.test(matRandom)
names(testResult)
testResult$psi

Class ConcordanceTest

Description

This class stores results obtained from a concordance test.

Details

Class ConcordanceTest stores results from a concordance test.

Slots

pvalue

The pvalue

psi1

The concordance in matrix x

psi2

The concordance in matrix y

method

The method used to obtain the pvalue

alternative

The alternative hypothesis

ci.lower

The lower confidence boudary

ci.upper

The upper confidence boudary

ci.method

The method used to obtain the confidence interval

alpha

The significance level

call

The call made to the concordance.test function

Extract test results from the results of a concordance.test

Description

coef extract the test results from the results of a concordance.test

Usage

## S4 method for signature 'ConcordanceTest'
coef(object, ...)

Arguments

Value

A matrix

See Also

Other concordance functions: concordance.test(), getPsi(), rfromPsi()

Examples

matRandom <- matrix(rnorm(3*20),20,3)
testResult <- concordance.test(matRandom)
getPsi(testResult)
coef(testResult)

Perform a nonparametric concordance test.

Description

concordance.test performs a test for a random concordance (if a single matrix is given) or tests for equal concordance between two matrices.

Usage

concordance.test(x, y = NULL, alternative = NULL, alpha = 0.05, ...)

Arguments

Details

• Testing the deviation from random concordance: if only one matrix is given (i.e. argument x), its concordance will be tested against the alternative hypothesis of finding a higher concordance under random sampling conditions. For small matrices (depending on number of replicate measurements) an exact method will be used to determine a p-value. In case of larger matrices, where the exact approach in not feasible, either the revised-beta approach (default), a beta approximation, or a normal approximation is used. To enforce the use of either one method, the method argument can be used with value "exact","Rbeta","beta" or "normal".

• Testing for a difference between concordances: if both arguments x and y have been given, the equality of concordances of both matrices is tested. The default alternative hypothesis is 'two.sided'. Both matrices must be of equal size and have corresponding missing entries (NA values). In case of missing data in one matrix, the same entries in the other matrix will also be set to missing. This method involves bootstrapping to estimate variance and confidence estimates, with adjustable options via the global R options "nopaco.nCPU" (default=2), "nopaco.nDraws.CI" (default=1e4) and "nopaco.seed" (default = 1).

Unbalanced data due to randomly missing data or an unequal number of repeated measurements per subject is allowed. In that case, missing or unknown values must be set to NA.

Value

An object of ConcordanceTest-class

References

P.Rothery (1979) Biometrika 66(3):629-639

See Also

Other concordance functions: coef(), getPsi(), rfromPsi()

Examples

require(MASS) ##to use the 'mvrnorm' function

#Generate a matrix without concordance
# for three observers in two samples
matRandom <- matrix(rnorm(3*20),20,3)
concordance.test(matRandom) 

#Generate a corresponding matrix with strong concordance
sigma<-matrix(0.8,3,3)
diag(sigma)<-1
matConcordant <- mvrnorm(20,mu=rep(0,3),Sigma=sigma)
concordance.test(matConcordant)

#Test concordances between the two matrices
aTest <- concordance.test(matConcordant, matRandom)

getPsi(aTest)
coef(aTest)

Obtain concordance coefficients.

Description

getPsi returns the concordance coefficient(s) from a matrix or a result obtained by the concordance.test function.

Usage

getPsi(x, y, ...)

## S4 method for signature 'ConcordanceTest,missing'
getPsi(x)

## S4 method for signature 'matrix,missing'
getPsi(x, y, ...)

## S4 method for signature 'data.frame,missing'
getPsi(x, y, ...)

## S4 method for signature 'data.frame,data.frame'
getPsi(x, y, ...)

## S4 method for signature 'matrix,NULL'
getPsi(x, y, ...)

## S4 method for signature 'matrix,matrix'
getPsi(x, y, ...)

Arguments

Value

A numeric vector with coefficient(s)

References

P.Rothery (1979) Biometrika 66(3):629-639

See Also

Other concordance functions: coef(), concordance.test(), rfromPsi()

Examples

matRandom <- matrix(rnorm(30),10,3)
testResult <- concordance.test(matRandom)
getPsi(testResult)
getPsi(matRandom)

Extract argument names from a ConcordanceTest object

Description

names extracts argument names from a ConcordanceTest-class object

Usage

## S4 method for signature 'ConcordanceTest'
names(x)

Arguments

Value

A character vector

Examples

matRandom <- matrix(rnorm(3*20),20,3)
testResult <- concordance.test(matRandom)
names(testResult)

Convertion between Pearson correlation and the non paramtric concordance coefficient

Description

Convertion between Pearson correlation and the non paramtric concordance coefficient

Usage

rfromPsi(psi)

psifromR(r)

Arguments

Details

The convertion is performed following the relationship described by Rothery (1979). 2*cos(pi*(1-psi))-1

Value

A (vector of) corresponding Pearson correlation coefficient(s).

References

Rothery, P. 'A nonparametric measure of intraclass correlation', Biometrika, 66, 3, 629-639 (1979).

See Also

Other concordance functions: coef(), concordance.test(), getPsi()

Examples

#Generate a matrix without concordance
matRandom <- matrix(rnorm(30),10,3)
result<-concordance.test(matRandom)
getPsi(result) #concordance coefficient
result$ci      #95% confidence interval

#Corresonding Pearson correlation
rfromPsi(getPsi(result))
rfromPsi(result$ci)

#Plot the relation between Pearson correlation and the nonparamatric concordance coefficient.
r<-seq(-1,1,0.01)
psi<-psifromR(r)
plot(r,psi,type='l',xlab="Pearson correlation", ylab="nonparametric concordance")

Hypothetical data of outcomes for two risk models

Description

This data is generated as explained in the nopaco vignette. It represents the outcomes of the risk models (model A and model B). Both models were applied to gene expression profiles 100 subjects, each run in duplo.

Usage

data(scores)

Format

A list with two elements named 'modelA' and 'modelB' both containing a dataframe with outcome scores for 100 subjects in the rows each having two replicate measurements in the columns.

Source

vignette("nopaco", package = "nopaco")

Examples

data(scores)
str(scores)
plot(scores[['modelA']])
plot(scores[['modelB']])