tidy.kappa: Tidy a(n) kappa object

Description

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.

Usage

# S3 method for kappa
tidy(x, ...)

Arguments

A kappa object returned from psych::cohen.kappa().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.level = 0.9, all computation will proceed using conf.level = 0.95. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.

Value

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`.

Details

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.

Examples

Run this code

# NOT RUN {
library(psych)

rater1 <- 1:9
rater2 <- c(1, 3, 1, 6, 1, 5, 5, 6, 7)
ck <- cohen.kappa(cbind(rater1, rater2))

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))
# }