kripp.alpha {irr} | R Documentation |
Calculates the alpha coefficient of reliability proposed by Krippendorff (1980).
kripp.alpha(x, method = c("nominal", "ordinal", "interval", "ratio"))
x |
n*m matrix or dataframe, n objects m raters. |
method |
data level of ratings, you can specify just the initial letter. |
A list with class '"irrlist"' containing the following components:
$method |
a character string describing the method. |
$subjects |
the number of data objects. |
$raters |
the number of raters. |
$irr.name |
a character string specifying the name of the coefficient. |
$value |
value of alpha. |
$stat.name |
here "nil" as there is no test statistic. |
$statistic |
the value of the test statistic (NULL). |
$p.value |
the probability of the test statistic (NULL). |
coincidence.matrix |
the concordance/discordance matrix used in the calculation of alpha |
data.values |
a character vector of the unique data values |
levx |
the unique values of the ratings |
nmatchval |
the count of matches, used in calculation |
data.level |
the data level of the ratings ("nominal","ordinal", "interval","ratio") |
Krippendorff's alpha coefficient is particularly useful where the level of measurement of classification data is higher than nominal or ordinal.
Jim Lemon
Krippendorff, K. (1980) Content analysis: An introduction to its methodology. Beverly Hills, CA: Sage.
icc
,
meancor
,
kendall
,
kappam.fleiss
# the "C" data from Krippendorff nmm <- matrix(c( 1, 1,NA, 1, 2, 2, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 1, 2, 3, 4, 4, 4, 4, 4, 1, 1, 2, 1, 2, 2, 2, 2, NA, 5, 5, 5,NA,NA, 1, 1,NA,NA, 3,NA),nrow=12,byrow=TRUE) # first assume the default nominal classification kripp.alpha(nmm) # now use the same data with the other three methods kripp.alpha(nmm, "ordinal") kripp.alpha(nmm, "interval") kripp.alpha(nmm, "ratio")