epi.occc {epiR}

Overall concordance correlation coefficient (OCCC)

Description

Overall concordance correlation coefficient (OCCC) for agreement on a continuous measure based on Lin (1989, 2000) and Barnhart et al. (2002).

Usage

epi.occc(dat, na.rm = FALSE, pairs = FALSE)

## S3 method for class 'epi.occc'
print(x, ...)

## S3 method for class 'epi.occc'
summary(object, ...)

Arguments

dat

a matrix, or a matrix like object. Rows correspond to cases/observations, columns corresponds to raters/variables.

na.rm

logical. Should missing values (including NaN) be removed?

pairs

logical. Should the return object contain pairwise statistics? See Details.

x, object

an object of class epi.occc.

...

further arguments passed to print methods.

Details

The index proposed by Barnhart et al. (2002) is the same as the index suggested by Lin (1989) in the section of future studies with a correction of a typographical error in Lin (2000).

Value

An object of class epi.occc with the following elements (notation follows Barnhart et al. 2002):

occc:

the value of the overall concordance correlation coefficient, \rho_{o}^{c}

oprec:

overall precision, \rho

oaccu:

overall accuracy, \chi^{a}

data.name:

name of the input data, dat.

If pairs = TRUE a list with the following elements. Column indices for the pairs (j,k) follow lower-triangle column-major rule based on a ncol(x) times ncol(x) matrix):

ccc:

pairwise CCC values, \rho_{jk}^{c}

prec:

pairwise precision values, \rho_{jk}

accu:

pairwise accuracy values, \chi_{jk}^{a}

ksi:

pairwise weights, \xi_{jk}

scale:

pairwise scale values, v_{jk}

location:

pairwise location values, u_{jk}

Author(s)

Peter Solymos, [e-mail].

References

Barnhart H X, Haber M, Song J (2002). Overall concordance correlation coefficient for evaluating agreement among multiple observers. Biometrics 58: 1020 - 1027.

Lin L (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics 45: 255 - 268.

Lin L (2000). A note on the concordance correlation coefficient. Biometrics 56: 324 - 325.

See Also

epi.ccc

Examples

## EXAMPLE 1:
## Generate some rating data:

## Not run: 
set.seed(1234)
p <- runif(n = 10, min = 0, max = 1)
x <- replicate(n = 5, expr = rbinom(n = 10, size = 4, prob = p) + 1)

rval.occc01 <- epi.occc(dat = x, pairs = TRUE)
print(rval.occc01); summary(rval.occc01)

## End(Not run)