Compute power of test or determine parameters to obtain target
power (same as power.anova.test).
power.chisq.test(n = NULL, w = NULL, df = NULL, sig.level = 0.05, power = NULL)total number of observations.
effect size.
degree of freedom (depends on the chosen test.
Significance level (Type I error probability).
Power of test (1 minus Type II error probability).
Object of class "power.htest", a list of the arguments (including the computed one) augmented with 'method' and 'note' elements.
Exactly one of the parameters w, n, power or
sig.level must be passed as NULL, and this parameter is
determined from the others. Note that the last one has non-NULL
default, so NULL must be explicitly passed, if you want to compute
it.
Cohen, J. (1988) Statistical power analysis for the behavioral sciences (2nd ed.) Hillsdale, NJ: Lawrence Erlbaum.
# NOT RUN {
## Exercise 7.1 P. 249 from Cohen (1988)
power.chisq.test(w=0.289, df=(4-1), n=100, sig.level=0.05)
## Exercise 7.3 p. 251
power.chisq.test(w=0.346, df=(2-1)*(3-1), n=140, sig.level=0.01)
## Exercise 7.8 p. 270
power.chisq.test(w=0.1, df=(5-1)*(6-1), power=0.80, sig.level=0.05)
# }
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