KrippAlpha {DescTools} | R Documentation |

## Krippendorff's Alpha Reliability Coefficient

### Description

Calculate the alpha coefficient of reliability proposed by Krippendorff.

### Usage

```
KrippAlpha(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. https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-016-0200-9

### Note

This function was previously published as `kripp.alpha()`

in the irr package and has been
integrated here without logical changes, but with some adaptations in the result structure.

### Author(s)

Jim Lemon <jim@bitwrit.com.au>

### References

Krippendorff, K. (1980) *Content analysis: An introduction to its methodology*. Beverly Hills, CA: Sage.

### See Also

`CronbachAlpha`

, `KappaM`

, `CohenKappa`

### 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
KrippAlpha(nmm)
# now use the same data with the other three methods
KrippAlpha(nmm, "ordinal")
KrippAlpha(nmm, "interval")
KrippAlpha(nmm, "ratio")
```

*DescTools*version 0.99.54 Index]