| tidy.kappa | R Documentation | 
Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
## S3 method for class 'kappa'
tidy(x, ...)
| x | A  | 
| ... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in  
 | 
Note that confidence level (alpha) for the confidence interval
cannot be set in tidy. Instead you must set the alpha argument
to psych::cohen.kappa() when creating the kappa object.
A tibble::tibble() with columns:
| conf.high | Upper bound on the confidence interval for the estimate. | 
| conf.low | Lower bound on the confidence interval for the estimate. | 
| estimate | The estimated value of the regression term. | 
| type | Either 'weighted' or 'unweighted'. | 
tidy(), psych::cohen.kappa()
# load libraries for models and data
library(psych)
# generate example data
rater1 <- 1:9
rater2 <- c(1, 3, 1, 6, 1, 5, 5, 6, 7)
# fit model
ck <- cohen.kappa(cbind(rater1, rater2))
# summarize model fit with tidiers + visualization
tidy(ck)
# graph the confidence intervals
library(ggplot2)
ggplot(tidy(ck), aes(estimate, type)) +
  geom_point() +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high))
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