Calculate reliability measures based on content analysis

This function calculates different reliability measures which are based on the empirical research method of content analysis.

Usage

get_coder_metrics(
  true_values = NULL,
  predicted_values = NULL,
  return_names_only = FALSE
)

true_values: factor containing the true labels/categories.
predicted_values: factor containing the predicted labels/categories.
return_names_only: bool If TRUE returns only the names of the resulting vector. Use FALSE to request computation of the values.

If return_names_only = FALSE returns a vector with the following reliability measures:

iota_index: Iota Index from the Iota Reliability Concept Version 2.
min_iota2: Minimal Iota from Iota Reliability Concept Version 2.
avg_iota2: Average Iota from Iota Reliability Concept Version 2.
max_iota2: Maximum Iota from Iota Reliability Concept Version 2.
min_alpha: Minmal Alpha Reliability from Iota Reliability Concept Version 2.
avg_alpha: Average Alpha Reliability from Iota Reliability Concept Version 2.
max_alpha: Maximum Alpha Reliability from Iota Reliability Concept Version 2.
static_iota_index: Static Iota Index from Iota Reliability Concept Version 2.
dynamic_iota_index: Dynamic Iota Index Iota Reliability Concept Version 2.
kalpha_nominal: Krippendorff's Alpha for nominal variables.
kalpha_ordinal: Krippendorff's Alpha for ordinal variables.
kendall: Kendall's coefficient of concordance W with correction for ties.
c_kappa_unweighted: Cohen's Kappa unweighted.
c_kappa_linear: Weighted Cohen's Kappa with linear increasing weights.
c_kappa_squared: Weighted Cohen's Kappa with quadratic increasing weights.
kappa_fleiss: Fleiss' Kappa for multiple raters without exact estimation.
percentage_agreement: Percentage Agreement.
balanced_accuracy: Average accuracy within each class.
gwet_ac: Gwet's AC1/AC2 agreement coefficient.

If return_names_only = TRUE returns only the names of the vector elements.