Description Usage Arguments Value Note Author(s) References Examples

calculates the alpha coefficient of reliability proposed by Krippendorff

1 | ```
kripp.alpha(x, method=c("nominal","ordinal","interval","ratio"))
``` |

`x` |
classifier x object matrix of classifications or scores |

`method` |
data level of x |

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") |

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.

1 2 3 4 5 6 7 8 9 | ```
# 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")
``` |

```
Loading required package: lpSolve
Krippendorff's alpha
Subjects = 12
Raters = 4
alpha = 0.743
Krippendorff's alpha
Subjects = 12
Raters = 4
alpha = 0.815
Krippendorff's alpha
Subjects = 12
Raters = 4
alpha = 0.849
Krippendorff's alpha
Subjects = 12
Raters = 4
alpha = 0.797
```

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