statsmodels.stats.rates.test_poisson_2indep¶

statsmodels.stats.rates.test_poisson_2indep(count1, exposure1, count2, exposure2, ratio_null=1, method='score', alternative='two-sided', etest_kwds=None)[source]¶

test for ratio of two sample Poisson intensities

If the two Poisson rates are g1 and g2, then the Null hypothesis is

H0: g1 / g2 = ratio_null

against one of the following alternatives

H1_2-sided: g1 / g2 != ratio_null
H1_larger: g1 / g2 > ratio_null
H1_smaller: g1 / g2 < ratio_null

Parameters

count1int

Number of events in first sample.

exposure1float

Total exposure (time * subjects) in first sample.

count2int

Number of events in second sample.

exposure2float

Total exposure (time * subjects) in second sample.

ratio: float

ratio of the two Poisson rates under the Null hypothesis. Default is 1.

methodstr

Method for the test statistic and the p-value. Defaults to ‘score’. Current Methods are based on Gu et. al 2008. Implemented are ‘wald’, ‘score’ and ‘sqrt’ based asymptotic normal distribution, and the exact conditional test ‘exact-cond’, and its mid-point version ‘cond-midp’. method=’etest’ and method=’etest-wald’ provide pvalues from etest_poisson_2indep using score or wald statistic respectively. see Notes.

alternativestr

The alternative hypothesis, H1, has to be one of the following

‘two-sided’: H1: ratio of rates is not equal to ratio_null (default)
‘larger’ : H1: ratio of rates is larger than ratio_null
‘smaller’ : H1: ratio of rates is smaller than ratio_null

etest_kwds: dictionary

Additional parameters to be passed to the etest_poisson_2indep funtcion, namely ygrid.

Returns

resultsinstance of HolderTuple class: The two main attributes are test statistic statistic and p-value pvalue.