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2013-08-22T11:47:50.353
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Some of the basic power calculations are now available in statsmodels <a href="http://statsmodels.sourceforge.net/devel/stats.html#power-and-sample-size-calculations" rel="noreferrer">http://statsmodels.sourceforge.net/devel/stats.html#power-and-sample-size-calculations</a> <a href="http://jpktd.blogspot.ca/2013/03/statistical-power-in-statsmodels.html" rel="noreferrer">http://jpktd.blogspot.ca/2013/03/statistical-power-in-statsmodels.html</a> The blog article does not yet take the latest changes to the statsmodels code into account. Also, I haven't decided yet how many wrapper functions to provide, since many power calculations just reduce to the basic distribution. <pre><code>>>> import statsmodels.stats.api as sms >>> es = sms.proportion_effectsize(0.5, 0.75) >>> sms.NormalIndPower().solve_power(es, power=0.9, alpha=0.05, ratio=1) 76.652940372066908 </code></pre> In R stats <pre><code>> power.prop.test(p1 = .50, p2 = .75, power = .90) Two-sample comparison of proportions power calculation n = 76.7069301141077 p1 = 0.5 p2 = 0.75 sig.level = 0.05 power = 0.9 alternative = two.sided NOTE: n is number in *each* group </code></pre> using R's <code>pwr</code> package <pre><code>> library(pwr) > h<-ES.h(0.5,0.75) > pwr.2p.test(h=h, power=0.9, sig.level=0.05) Difference of proportion power calculation for binomial distribution (arcsine transformation) h = 0.5235987755982985 n = 76.6529406106181 sig.level = 0.05 power = 0.9 alternative = two.sided NOTE: same sample sizes </code></pre>
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1. POIs there a python (scipy) function to determine parameters needed to obtain a target power?
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