statsmodels.stats.proportion.proportions_ztost¶

statsmodels.stats.proportion.proportions_ztost(count, nobs, low, upp, prop_var='sample')[source]¶

Equivalence test based on normal distribution

Parameters:¶

count : {int, array_like}¶

the number of successes in nobs trials. If this is array_like, then the assumption is that this represents the number of successes for each independent sample

nobs : int¶

the number of trials or observations, with the same length as count.

low : float¶

equivalence interval low < prop1 - prop2 < upp

upp : float¶

equivalence interval low < prop1 - prop2 < upp

prop_var : str or float in (0, 1)¶

prop_var determines which proportion is used for the calculation of the standard deviation of the proportion estimate The available options for string are ‘sample’ (default), ‘null’ and ‘limits’. If prop_var is a float, then it is used directly.

Returns:¶

• pvalue (float) – pvalue of the non-equivalence test

• t1, pv1 (tuple of floats) – test statistic and pvalue for lower threshold test

• t2, pv2 (tuple of floats) – test statistic and pvalue for upper threshold test

Notes

checked only for 1 sample case