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 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:
Upper bound on the confidence interval for the estimate.
Lower bound on the confidence interval for the estimate.
The estimated value of the regression term.
Either `weighted` or `unweighted`.
if (requireNamespace("psych", quietly = TRUE)) { 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)) } #> #> Attaching package: ‘psych’ #> The following object is masked from ‘package:boot’: #> #> logit #> The following object is masked from ‘package:car’: #> #> logit #> The following object is masked from ‘package:drc’: #> #> logistic #> The following objects are masked from ‘package:ggplot2’: #> #> %+%, alpha #> The following object is masked from ‘package:mclust’: #> #> sim