a matrix of observations with one subject per row and one
rater per column.
conf.level
confidence level of the interval. The default
is 0.95.
method
a character string specifying the method used to
obtain the estimate of the CCC.
It must be one of "jackknifeZ", "jackknife", "bootstrap",
"bootstrapBC", "mvn.jeffreys", "mvn.conjugate","mvt",
and "lognormalNormal",
and may be abbreviated. The default is "jackknifeZ".
nboot
number of bootstrap replicates. The default value is 999.
nmcmc
number of iterations used in the Bayesian approach. The
default value is 10000.
mvt.para
values of hyper-parameters and initial values of
parameters for multivariate t (MVT) distribution.
lower.v is the lower bound of degrees of freedom (df) of the MVT.
upper.v is the upper bound of df of the MVT.
Mu0 is the mean vector of multivariate normal prior of the
location of the MVT and the default value is 0.
Sigma0 is the variance matrix of multivariate normal prior of
the location of the MVT and the default value is a diagonal matrix with
diagonal entries equal to 10000.
p is the df of wishart prior of inverse of the scale matrix
of the MVT and the default value is the number of raters.
V is the scale matrix of wishart prior of inverse of the scale
matrix of the MVT and the default value is identity matrix.
v is the initial value of the df of the MVT. Its default is
NULL and for the default, the value will be generated by using
the ECME Algorithm.
Sigma is the initial value of the scale matrix of the MVT.
Its default is NULL and for the default, the value will be
generated by using the ECME Algorithm.
NAaction
a character string specifying what should happen
when the data contain NAs. It must be one of "fail"
and "omit" and may be abbreviated. The default is "fail" that causes
the function to print an error message and terminate if there are
any incomplete observations. If it is "omit", then the entire row(s)
containing incomplete observation(s) will be deleted.
Details
To obtain point estimate and confidence interval, the methods available include the
jackknife method with and without Z-transformation, the bootstrap,
and the Bayesian approach for the multivariate t, multivariate
normal and lognormal-normal distributions.
Value
Point estimate and lower and upper bounds of the confidence
interval of the CCC.
References
Dai Feng, Richard Baumgartner and Vladimir Svetnik (2015)
A Bayesian estimate of the concordance correlation coefficient with skewed data.
Pharmaceutical Statistics,
DOI: 10.1002/pst.1692
Dai Feng, Richard Baumgartner and Vladimir Svetnik (2015)
A robust Bayesian estimate of the concordance correlation coefficient.
Journal of Biopharmaceutical Statistics25(3) 490-507,
DOI: 10.1080/10543406.2014.920342
Dai Feng, Vladimir Svetnik, Alexandre Coimbra and Richard Baumgartner (2014)
A comparison of confidence interval methods for the concordance
correlation coefficient and intraclass correlation coefficient with
small number of raters.
Journal of Biopharmaceutical Statistics24(2) 272-293,
DOI: 10.1080/10543406.2013.863780.
Dai Feng, Richard Baumgartner and Vladimir Svetnik (2014)
A short note on jackknifing the concordance correlation coefficient.
Statistics in Medicine33(3) 514-516, DOI: 10.1002/sim.5931
Lawrence I-Kuei Lin (1989)
A concordance correlation coefficient to evaluate reproducibility.
Biometrics45 255-268