FTestPower.power()

statsmodels.stats.power.FTestPower.power

FTestPower.power(effect_size, df_num, df_denom, alpha, ncc=1) [source]

Calculate the power of a F-test.

Parameters:

effect_size : float standardized effect size, mean divided by the standard deviation. effect size has to be positive. df_num : int or float numerator degrees of freedom. df_denom : int or float denominator degrees of freedom. alpha : float in interval (0,1) significance level, e.g. 0.05, is the probability of a type I error, that is wrong rejections if the Null Hypothesis is true. ncc : int degrees of freedom correction for non-centrality parameter. see Notes

Returns:

power : float 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.

Notes

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)