prec_kappa: Sample size or precision for Cohen's kappa

In presize: Precision Based Sample Size Calculation

Sample size or precision for Cohen's kappa

Description

prec_kappa returns the sample size or the precision for the provided Cohen's kappa coefficient.

Usage

prec_kappa(
  kappa,
  n = NULL,
  raters = 2,
  n_category = 2,
  props,
  conf.width = NULL,
  conf.level = 0.95
)

Arguments

kappa	expected value of Cohen's kappa.
n	sample size.
raters	number of raters (maximum of 6).
n_category	number of categories of outcomes (maximum of 5).
props	expected proportions of each outcome (should have length n_category).
conf.width	precision (the full width of the confidence interval).
conf.level	confidence level.

Details

This function wraps the FixedN and CI functions in the kappaSize package. The FixedN functions in kappaSize return a one sided confidence interval. The values that are passed to kappaSize ensure that two-sided confidence intervals are returned, although we assume that confidence intervals are symmetrical.

Value

Object of class "presize", a list of arguments (including the computed one) augmented with method and note elements.

See Also

FixedNBinary, FixedN3Cats, CIBinary, CI3Cats

Examples

# precision based on sample size
#   two categories with proportions of 30 and 70\%, four raters
prec_kappa(kappa = .5, n = 200, raters = 4, n_category = 2, props = c(.3,.7))
# sample size to get a given precision
prec_kappa(kappa = .5, conf.width = .15, raters = 4, n_category = 2,
           props = c(.3,.7))

# as above, but with two scenarios for kappa
prec_kappa(kappa = c(.5, .75), conf.width = .15, raters = 4, n_category = 2,
           props = c(.3,.7))
prec_kappa(kappa = c(.5, .75), conf.width = c(.15, 0.3), raters = 4,
           n_category = 2, props = c(.3,.7))

presize documentation built on March 7, 2023, 8:28 p.m.