statsmodels.stats.weightstats.ttost_paired¶
- statsmodels.stats.weightstats.ttost_paired(x1, x2, low, upp, transform=None, weights=None)[source]¶
test of (non-)equivalence for two dependent, paired sample
TOST: two one-sided t tests
null hypothesis: md < low or md > upp alternative hypothesis: low < md < upp
where md is the mean, expected value of the difference x1 - x2
If the pvalue is smaller than a threshold,say 0.05, then we reject the hypothesis that the difference between the two samples is larger than the the thresholds given by low and upp.
- Parameters:
- x1array_like
first of the two independent samples
- x2array_like
second of the two independent samples
- low, upp
float
equivalence interval low < mean of difference < upp
- weights
None
orndarray
case weights for the two samples. For details on weights see
DescrStatsW
- transform
None
orfunction
If None (default), then the data is not transformed. Given a function sample data and thresholds are transformed. If transform is log the the equivalence interval is in ratio: low < x1 / x2 < upp
- Returns: