Agreement Coefficents

agree_coef produces inter-rater reliability or "agreement coefficients" as described by Gwet.

Usage

agree_coef(
  wide = TRUE,
  col.names = NULL,
  measure,
  item,
  id,
  data,
  weighted = FALSE,
  conf.level = 0.95
)

Arguments

wide

Logical value (TRUE or FALSE) indicating if data is in a "wide" format. Default is TRUE.

col.names

If wide is equal to TRUE then col.names is a list of the column names containing the measurements for reliability analysis.

measure

Name of column containing the measurement of interest.

item

Name of column containing the items. If this is an inter-rater reliability study then this would indicate the rater (e.g., rater1, rater2, rater3, etc).

id

Column with subject identifier.

data

Data frame with all data.

weighted

Logical value (TRUE or FALSE) indicating whether to weight the responses. If TRUE (default is FALSE) then quadratic weights are utilized. This option should be set to TRUE for ordinal or continuous responses.

conf.level

the confidence level required. Default is 95%.

Value

Returns single data frame of inter-rater reliability coefficients.

References

Gwet, K.L. (2014, ISBN:978-0970806284). “Handbook of Inter-Rater Reliability,” 4th Edition. Advanced Analytics, LLC. Gwet, K. L. (2008). “Computing inter-rater reliability and its variance in the presence of high agreement," British Journal of Mathematical and Statistical Psychology, 61, 29-48.

Examples

data('reps')
agree_coef(data = reps, wide = TRUE, col.names = c("x","y"), weighted = TRUE)
#>                              est         se   lower.ci  upper.ci
#> Percent Agreement      0.9131459 0.07673687 0.75253380 1.0000000
#> Gwet's AC2             0.5073626 0.18354840 0.12319136 0.8915338
#> Fleiss' Kappa          0.5255860 0.17484095 0.15963973 0.8915324
#> Kririppendorff's Alpha 0.4771011 0.19501219 0.06566137 0.8885409