statsmodels.stats.power.FTestPower¶
- class statsmodels.stats.power.FTestPower(**kwds)[source]¶
Statistical Power calculations for generic F-test of a constraint
This class is not recommended, use FTestPowerF2 with corrected interface.
This is based on Cohen’s f as effect size measure.
Warning: Methods in this class have the names df_num and df_denom reversed.
See also
FTestPowerF2
Class with Cohen’s f-squared as effect size, corrected keyword names.
Examples
Sample size and power for multiple regression base on R-squared
Compute effect size from R-squared
>>> r2 = 0.1 >>> f2 = r2 / (1 - r2) >>> f = np.sqrt(f2) >>> r2, f2, f (0.1, 0.11111111111111112, 0.33333333333333337)
Find sample size by solving for denominator df, wrongly named
df_num
>>> df1 = 1 # number of constraints in hypothesis test >>> df2 = FTestPower().solve_power(effect_size=f, alpha=0.1, power=0.9, df_denom=df1) >>> ncc = 1 # default >>> nobs = df2 + df1 + ncc >>> df2, nobs (76.46459758305376, 78.46459758305376)
verify power at df2
>>> FTestPower().power(effect_size=f, alpha=0.1, df_denom=df1, df_num=df2) 0.8999999972109698
Methods
plot_power
([dep_var, nobs, effect_size, ...])Plot power with number of observations or effect size on x-axis
power
(effect_size, df_num, df_denom, alpha)Calculate the power of a F-test.
solve_power
([effect_size, df_num, df_denom, ...])solve for any one parameter of the power of a F-test