statsmodels.stats.proportion.proportion_effectsize
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statsmodels.stats.proportion.proportion_effectsize(prop1, prop2, method='normal')
[source] -
effect size for a test comparing two proportions
for use in power function
Parameters: prop1, prop2: float or array_like :
Returns: es : float or ndarray
effect size for (transformed) prop1 - prop2
Notes
only method=?normal? is implemented to match pwr.p2.test see http://www.statmethods.net/stats/power.html
Effect size for
normal
is defined as2 * (arcsin(sqrt(prop1)) - arcsin(sqrt(prop2)))
I think other conversions to normality can be used, but I need to check.
Examples
>>> smpr.proportion_effectsize(0.5, 0.4) 0.20135792079033088 >>> smpr.proportion_effectsize([0.3, 0.4, 0.5], 0.4) array([-0.21015893, 0. , 0.20135792])
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