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DoWhy 0.9 includes some exciting new extensions and features, including better sensitivity analyses, new identification algorithms, and more. I'm particularly excited to see so many new contributors joining in on this release!
#causality #causalinf #causaltwitter
#causality #causalinf #causaltwitter
Ezequiel Smucler (@hazqiyal) adds an identification algorithm to find optimal backdoor adjustment sets that yield estimators with smallest asymptotic variance
pywhy.org/dowhy/v0.9/exa…
pywhy.org/dowhy/v0.9/exa…
Jeffrey Gleason adds e-value sensitivity analysis pywhy.org/dowhy/v0.9.1/e…
and Anusha0409 adds sensitivity analysis for non-parametric estimators: pywhy.org/dowhy/v0.9.1/e…
and Anusha0409 adds sensitivity analysis for non-parametric estimators: pywhy.org/dowhy/v0.9.1/e…
@MaxJordan_N @EpiEllie @AmakaEMD @DrDeidraCrews That sounds reasonable. Admittedly I am not trained in genetic epi, so I may be totally off-base and welcome correction. Let’s say there are a bunch of genetic variants that increase risk of hypertension. Holding all else equal (waving hands), 2 increase risk by same degree 1/
@MaxJordan_N @EpiEllie @AmakaEMD @DrDeidraCrews Variant A is represented at 4% among a US Black same, 8% among an insular European sample that’s often studied. Variant B is present in 4% of US Black sample and 0% in European samples (my understanding is that people of African descent in US more genetically varied than...
@MaxJordan_N @EpiEllie @AmakaEMD @DrDeidraCrews ...most “White” populations as conceptualized in these US sense so I think this is plausible. So here there is some relationship between the “race” node and genetic variants bc of all the processes that have grouped people and structured society. But it’s not a 1-1 overlap.
