- FTestPower.power(effect_size, df_num, df_denom, alpha, ncc=1)¶
Calculate the power of a F-test.
standardized effect size, mean divided by the standard deviation. effect size has to be positive.
numerator degrees of freedom.
denominator degrees of freedom.
significance level, e.g. 0.05, is the probability of a type I error, that is wrong rejections if the Null Hypothesis is true.
degrees of freedom correction for non-centrality parameter. see Notes
Power of the test, e.g. 0.8, is one minus the probability of a type II error. Power is the probability that the test correctly rejects the Null Hypothesis if the Alternative Hypothesis is true.
sample size is given implicitly by df_num
set ncc=0 to match t-test, or f-test in LikelihoodModelResults. ncc=1 matches the non-centrality parameter in R::pwr::pwr.f2.test
ftest_power with ncc=0 should also be correct for f_test in regression models, with df_num and d_denom as defined there. (not verified yet)