Burnham, K.P., D.R. Anderson, G.C. White, C. Brownie and K.H. Pollock. 1987. Design and Analysis Methods for Fish Survival Experiments Based on Release-Recapture. Am. Fish. Soc. Monogr. 5, pages 216, 289-295.
The basic idea: Given the alternative model, Ha, is true, what is the probability that the likelihood-ratio test will reject the null model, Ho? If Ho is true, the power of the test should equal the significance level α.
Data should be generated by computing expected values under the alternative model for specified sample sizes, compute estimates under the alternative and null models, then compute a likelihood-ratio test between models. The likelihood-ratio test will give you the χ² value and degrees of freedom needed for the power analysis.
Specifically, the χ² value approximates the noncentrality parameter of a noncentral χ² distribution, from which power is directly obtained.
The formula used by the program is:
powr <- function(x2,df,alflvl) 1-pchisq(qchisq(1-alflvl,df),df,x2)
χ² : degrees-of-freedom : significance level(α):
: