Description Usage Arguments Details References

This function performs the paired t-test for testing the difference between two correlated Krippendorff's alpha coefficients for statistical significance. It implements the linearization method of Gwet (2016).

1 2 3 4 5 6 7 | ```
ttest.alpha(
g1.ratings,
g2.ratings,
weights = "unweighted",
conflev = 0.95,
N = Inf
)
``` |

`g1.ratings` |
is a mandatory parameter representing the first data frame of ratings. |

`g2.ratings` |
is a mandatory parameter representing the second data frame of ratings. |

`weights` |
is an optional parameter that defines the weights needed in a weighted analysis. It's default value is “unweighted” which requests the unweighted analysis. |

`conflev, ` |
is an optional parameter representing the confidence level. It's default value is 0.95. |

`N` |
is an optional parameter representing the size of the subject population. It's default value is infinity. |

This function takes 2 required parameters, which are the 2 groups of raters being compared: "g1.ratings" and "g2.ratings." Both datasets must have the exact same number of rows, and each column represents one rater and contains its ratings (numeric or alphabetic). The user must exclude all subjects that are not rated by any rater.

Krippendorff, K. (1970). “Estimating the reliability, systematic error, and
random error of interval data”. *Educational and Psychological
Measurement*, **30**, 61-70.

Gwet, K. L. (2016). “Testing the Difference of Correlated Agreement
Coefficients for Statistical Significance,” *Educational and
Psychological Measurement*, **76**(4) 609-637.

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