N2.cohen.kappa {irr}

Sample Size Calculation for Cohen's Kappa Statistic with more than one category

Description

This function calculates the required sample size for the Cohen's Kappa statistic when two raters have the same marginal. Note that any value of "kappa under null" in the interval [-1,1] is acceptable (i.e. k0=0 is a valid null hypothesis).

Usage

 N2.cohen.kappa(mrg, k1, k0, alpha=0.05, power=0.8, twosided=FALSE)

Arguments

mrg

a vector of marginal probabilities given by raters

k1

the true Cohen's Kappa statistic

k0

the value of kappa under the null hypothesis

alpha

type I error of test

power

the desired power to detect the difference between true kappa and hypothetical kappa

twosided

TRUE if test is two-sided

Value

Returns required sample size.

Author(s)

Puspendra Singh and Jim Lemon

References

Flack, V.F., Afifi, A.A., Lachenbruch, P.A., & Schouten, H.J.A. (1988). Sample size determinations for the two rater kappa statistic. Psychometrika, 53, 321-325.

See Also

N.cohen.kappa, kappa2

Examples

  require(lpSolve)
  # Testing H0: kappa = 0.4 vs. HA: kappa > 0.4 (=0.6) given that
  # Marginal Probabilities by two raters are (0.2, 0.25, 0.55).
  #
  # one sided test with 80% power:
  N2.cohen.kappa(c(0.2, 0.25, 0.55), k1=0.6, k0=0.4)								
  # one sided test with 90% power:
  N2.cohen.kappa(c(0.2, 0.25, 0.55), k1=0.6, k0=0.4, power=0.9)	  

  # Marginal Probabilities by two raters are (0.2, 0.05, 0.2, 0.05, 0.2, 0.3)
  # Testing H0: kappa = 0.1 vs. HA: kappa > 0.1 (=0.5) given that
  #
  # one sided test with 80% power:
  N2.cohen.kappa(c(0.2, 0.05, 0.2, 0.05, 0.2, 0.3), k1=0.5, k0=0.1)