View source: R/psych-tidiers.R
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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