broom (version 0.5.6)

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 cross 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

x

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.lvel = 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:

type

Either "weighted" or "unweighted"

estimate

The estimated value of kappa with this method

conf.low

Lower bound of confidence interval

conf.high

Upper bound of confidence interval

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.

See Also

tidy(), psych::cohen.kappa()

Examples

# 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))

# }