N2.cohen.kappa {irr} | R Documentation |
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).
N2.cohen.kappa(mrg, k1, k0, alpha=0.05, power=0.8, twosided=FALSE)
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 |
Returns required sample size.
Puspendra Singh and Jim Lemon
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.
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)