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The R-package kappaGold
is about agreement of nominal
scale raters. You can find various agreement measures (like Fleiss’
kappa) but the main focus of this package is on agreement where there is
a gold standard.
Sometimes, not all raters have equal status but there is an instance considered to speak the ground truth and we might want to estimate the agreement of the other raters with this gold standard.
For a single gold standard rater we build on the idea of Conger that the multi-rater kappa due to Light (1971) is actually a mean of all pairwise Cohen’s kappas. In the situation of a gold standard, we only consider the pairwise Cohen’s kappas of each rater with that gold standard.
The implementation of this measure of agreement with a gold standard
is found in the function kappam_gold
.
kappam_gold
expects a matrix of ratings with observations
in the row and raters in the columns. The gold standard rater is by
default taken from the 1st column. The delete-1 jackknife
method is used to get an estimate of bias and standard error.
In medicine, staging is the process of assessing the extent to which
a tumour has grown. Staging affets treatment choice, for instance, if
radiation is used or not. Pathological assessment is typically the
gold-standard while non-invasive imaging allows for easier and earlier
tumour staging by radiologists. Inspired by the OCUM-trial
on colorectal tumour staging the data set stagingData
carries the fictitious staging of 21 colorectal tumour patients by a
pathologist based on a histological sample (gold standard) and 5
different radiologists. The agreement of the radiologists (columns 2 to
6) with the pathological staging as gold standard can be estimated by
kappam_gold
:
library("kappaGold")
# 1st column corresponds to gold-standard
kappam_gold(kappaGold::stagingData)
#> $method
#> [1] "Averaged Cohen's Kappa with gold standard"
#>
#> $subjects
#> [1] 21
#>
#> $raters
#> [1] 5
#>
#> $categories
#> [1] 3
#>
#> $agreem
#> [1] 0.60952
#>
#> $value0
#> [1] 0.41429
#>
#> $value
#> [1] 0.42552
#>
#> $se_j
#> [1] 0.074303
#>
#> $conf.level
#> [1] 0.95
#>
#> $ci.lo
#> [1] 0.27989
#>
#> $ci.hi
#> [1] 0.57115
#>
#> $ci.width
#> [1] 0.29126
Entry agreem
is the mean pairwise agreement between the
raters (to be evaluated) and the gold standard rating. The entry
value0
shows the mean of all pairwise Cohen’s kappa between
the raters and the gold standard. Delete-1 jackknife gives an estimate
for bias and standard error. These quantities are used to get the
bias-corrected estimate value
which can be used as point
estimate and a 95% confidence interval.
The situation is more complicated when there are multiple gold
standard rater. Often this is necessary when the rating is difficult,
maybe because the rating scale is not well defined and the only gold
standard is the consensus of a group a experienced raters. For this
situation, the package kappaGold
has an implementation of
an agreement coefficient proposed by Vanbelle, S. and Albert, A.
Agreement between Two Independent Groups of Raters. Psychometrika 74,
477–491 (2009) https://doi.org/10.1007/s11336-009-9116-1.
Note that this method applies for any two groups of raters, i.e., it does not need the notion of gold standard here.
Besides estimating agreement, we might need to compare the agreement
between two groups. In KappaGold
, you can find the methods
for two cases:
kappa_test()
kappa_test_corr()
Package kappaGold
was initially released to CRAN in
September 2024 (v0.3.2). To install the current version, simply issue
install.packages("kappaGold")
in your R-session. The
development of the R-package kappaGold
is going on at Gitlab. With the help
of the remotes
-package you can install the development
version of package kappaGold
via:
::install_gitlab("imb-dev/kappa_gold@develop") remotes
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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