Description Usage Arguments Details Value Author(s) References See Also Examples
Computes Fleiss' Kappa as an index of interrater agreement between m raters on categorical data. Additionally, category-wise Kappas could be computed.
1 | kappam.fleiss(ratings, exact = FALSE, detail = FALSE)
|
ratings |
n*m matrix or dataframe, n subjects m raters. |
exact |
a logical indicating whether the exact Kappa (Conger, 1980) or the Kappa described by Fleiss (1971) should be computed. |
detail |
a logical indicating whether category-wise Kappas should be computed |
Missing data are omitted in a listwise way.
The coefficient described by Fleiss (1971) does not reduce to Cohen's Kappa (unweighted) for m=2 raters. Therefore, the exact Kappa coefficient, which is slightly higher in most cases, was proposed by Conger (1980).
The null hypothesis Kappa=0 could only be tested using Fleiss' formulation of Kappa.
A list with class '"irrlist"' containing the following components:
$method |
a character string describing the method applied for the computation of interrater reliability. |
$subjects |
the number of subjects examined. |
$raters |
the number of raters. |
$irr.name |
a character string specifying the name of the coefficient. |
$value |
value of Kappa. |
$stat.name |
a character string specifying the name of the corresponding test statistic. |
$statistic |
the value of the test statistic. |
$p.value |
the p-value for the test. |
$detail |
a table with category-wise kappas and the corresponding test statistics. |
Matthias Gamer
Conger, A.J. (1980). Integration and generalisation of Kappas for multiple raters. Psychological Bulletin, 88, 322-328.
Fleiss, J.L. (1971). Measuring nominal scale agreement among many raters. Psychological Bulletin, 76, 378-382.
Fleiss, J.L., Levin, B., & Paik, M.C. (2003). Statistical Methods for Rates and Proportions, 3rd Edition. New York: John Wiley & Sons.
1 2 3 4 5 6 | data(diagnoses)
kappam.fleiss(diagnoses) # Fleiss' Kappa
kappam.fleiss(diagnoses, exact=TRUE) # Exact Kappa
kappam.fleiss(diagnoses, detail=TRUE) # Fleiss' and category-wise Kappa
kappam.fleiss(diagnoses[,1:4]) # Fleiss' Kappa of raters 1 to 4
|
Loading required package: lpSolve
Fleiss' Kappa for m Raters
Subjects = 30
Raters = 6
Kappa = 0.43
z = 17.7
p-value = 0
Fleiss' Kappa for m Raters (exact value)
Subjects = 30
Raters = 6
Kappa = 0.442
Fleiss' Kappa for m Raters
Subjects = 30
Raters = 6
Kappa = 0.43
z = 17.7
p-value = 0
Kappa z p.value
1. Depression 0.245 5.192 0.000
2. Personality Disorder 0.245 5.192 0.000
3. Schizophrenia 0.520 11.031 0.000
4. Neurosis 0.471 9.994 0.000
5. Other 0.566 12.009 0.000
Fleiss' Kappa for m Raters
Subjects = 30
Raters = 4
Kappa = 0.489
z = 13
p-value = 0
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