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Gist b989c26735fde8214c19

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Aakeshavan
Last edited Sep 4, 2014
Created on Sep 4, 2014

This example demonstrates statistical power calculations for several genetic association models (DRAB1_sGMV, HLAB_ucca, HLAB_sGM, NFkb_WM) using R’s noncentral F distribution via the rpy2 interface, with power derived from effect sizes and sample sizes listed in a pandas DataFrame. It imports the `stats` package and uses `statsmodels.api` alongside scipy.stats, defining a custom `pf` function that calls R’s `qf` and `pf` functions to compute critical values and noncentral power. The notebook also loads precomputed intraclass correlation coefficients from a pickled file and displays the power table as an HTML-rendered pandas DataFrame.

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