kripp.alpha {irr} | R Documentation |
calculate Krippendorff's alpha reliability coefficient
Description
calculates the alpha coefficient of reliability proposed by Krippendorff
Usage
kripp.alpha(x, method=c("nominal","ordinal","interval","ratio"))
Arguments
x |
classifier x object matrix of classifications or scores |
method |
data level of x |
Value
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). |
cm |
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") |
Note
Krippendorff's alpha coefficient is particularly useful where the level of measurement of classification data is higher than nominal or ordinal.
Author(s)
Jim Lemon
References
Krippendorff, K. (1980). Content analysis: An introduction to its methodology. Beverly Hills, CA: Sage.
Examples
# 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=4)
# 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")