# statsmodels.stats.proportion.score_test_proportions_2indep¶

statsmodels.stats.proportion.score_test_proportions_2indep(count1, nobs1, count2, nobs2, value=None, compare='diff', alternative='two-sided', correction=True, return_results=True)[source]

score_test for two independent proportions

This uses the constrained estimate of the proportions to compute the variance under the Null hypothesis.

Parameters
count1, nobs1 :

count and sample size for first sample

count2, nobs2 :

count and sample size for the second sample

valuefloat

diff, ratio or odds-ratio under the null hypothesis. If value is None, then equality of proportions under the Null is assumed, i.e. value=0 for ‘diff’ or value=1 for either rate or odds-ratio.

comparestr in [‘diff’, ‘ratio’ ‘odds-ratio’]

If compare is diff, then the confidence interval is for diff = p1 - p2. If compare is ratio, then the confidence interval is for the risk ratio defined by ratio = p1 / p2. If compare is odds-ratio, then the confidence interval is for the odds-ratio defined by or = p1 / (1 - p1) / (p2 / (1 - p2)

return_resultsbool

If true, then a results instance with extra information is returned, otherwise a tuple with statistic and pvalue is returned.

Returns
resultsresults instance or tuple

If return_results is True, then a results instance with the information in attributes is returned. If return_results is False, then only statistic and pvalue are returned.

statisticfloat

test statistic asymptotically normal distributed N(0, 1)

pvaluefloat

p-value based on normal distribution

other attributes :