statsmodels.stats.oneway.confint_effectsize_oneway

statsmodels.stats.oneway.confint_effectsize_oneway(f_stat, df, alpha=0.05, nobs=None)[source]

Confidence interval for effect size in oneway anova for F distribution

This does not yet handle non-negativity constraint on nc. Currently only two-sided alternative is supported.

Parameters:

  • f_stat (float)

  • df (tuple) –

    degrees of freedom df = (df1, df2) where

    • df1 : numerator degrees of freedom, number of constraints

    • df2 : denominator degrees of freedom, df_resid

  • alpha (float, default 0.05)

  • nobs (int, default None)

Returns:

Class with effect size and confidence attributes

Return type:

Holder

Notes

The confidence interval for the noncentrality parameter is obtained by inverting the cdf of the noncentral F distribution. Confidence intervals for other effect sizes are computed by endpoint transformation.

R package effectsize does not compute the confidence intervals in the same way. Their confidence intervals can be replicated with

>>> ci_nc = confint_noncentrality(f_stat, df1, df2, alpha=0.1)
>>> ci_es = smo._fstat2effectsize(ci_nc / df1, df1, df2)

See also

confint_noncentrality