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Prikvačeni tweet
Check out these replications of epidemiology studies using the zEpid python library https://github.com/pzivich/zEpid-replications … Includes demonstrations of parametric g-formula and IPW
#Epidemiology#causalinferencePrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
zEpid proslijedio/la je Tweet
Achieving a full-coverage society means Medicare for All.https://twitter.com/sandrogalea/status/1224719774451527681 …
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Caveat: g-formula can also be used to solve the above issues. However outcome-model-based approaches don't solve all censoring mechanisms (see Section 8.5 of Hernan & Robins for an example)
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For a discussion of IPCW to correct for informative LTFU, I suggest https://www.ncbi.nlm.nih.gov/m/pubmed/26484424/ …
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For a published (and more in depth presentation) on the necessity of survey weights for the PACE I would recommend https://www.ncbi.nlm.nih.gov/m/pubmed/23855598/ …
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While survey weights won't address LTFU, that doesn't justify ignoring survey weights for a non-random sample. Rather we need to use an analytical approach to address informative LTFU & non-random sampling
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Summary: survey weights and censoring weights are meant to solve distinct issues. If you are interested in the population-ACE, and there informative LTFU and the sample is a non-random sample of the target pop. then something needs to be done for each issue
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Recently been involved in a disagreement on the necessity of survey weights. Particularly if there is LTFU then why bother using survey weights. I wrote a simple simulation to demonstrate why survey weights are needed and LTFU is a distinct issuehttps://github.com/pzivich/Python-for-Epidemiologists/blob/master/5_Random_Demonstrations/Survey-Weights.ipynb …
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zEpid proslijedio/la je Tweet
what's wrong with "the problem in American healthcare is the prices" framing
https://twitter.com/awgaffney/status/1222873616582422529 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
zEpid proslijedio/la je Tweet
Asked for a comparison of TMLE and double machine learning, this blog post comparing the two approaches in historical context came together quickly https://vanderlaan-lab.org/2019/12/24/cv-tmle-and-double-machine-learning/ …
#causalinference#statstwitter#epitwitter#machinelearninghttps://twitter.com/emaadmanzoor/status/1208924841316880385 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
zEpid proslijedio/la je Tweet
Today, the majority of this country, myself included, celebrates the birth of a Brown-skinned Jewish refugee and migrant, a major prophet in Islam, a socialist, a champion of equality, who preached against exorbitant wealth, hunger, homelessness, and hatred. Merry Christmas!
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Hey
#EpiTwitter what is your go-to estimator of the average treatment effect in your applied work?Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
zEpid proslijedio/la je Tweet
Getting a flu shot is praxis, solidarity, mutual aid, etc. — flu is very dangerous for people who can’t get vaccinated!! If you haven’t gotten your shot yet, go do it tomorrow, if not to spare yourself the flu then to protect those of us who can’t get the shot!!
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zEpid proslijedio/la je Tweet
In retaliation for 'one-hot coding', I propose we start calling deep learning 'multilevel regression'
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zEpid proslijedio/la je Tweet
now that dunking on Gates is a thing can we talk about the fact that he used his billions as leverage to effectively take over health policy for Africa and large parts of Asia and education policy in the US and no one ever voted for him and he’s accountable to literally no one.
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zEpid proslijedio/la je Tweet
Say Bill Gates was actually taxed $100 billion. We could end homelessness and provide safe drinking water to everyone in this country. Bill would still be a multibillionaire. Our message: the billionaire class cannot have it all when so many have so little.https://twitter.com/teddyschleifer/status/1192188119417704448 …
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zEpid proslijedio/la je Tweet
If I’ve said it once, I’ve said it a 1000 times. Instrumental variables assume no unmeasured confounding!! It’s just the confounding you care about is instrument & outcome, not exposure & outcome. If you don’t believe no unmeasured confounding is ever possible, stop using IVs!!
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v0.8.1 minor release now available TMLE supports PyGAM's LogisticGAM for custom_models now Note: TMLE will not lose support for ML in v0.9.0 but I am trying to see if I can check whether the input estimators are Donsker and generate a warning if not
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If you're at
#iaphs come listen to my talk on assortativity by treatment and bias in networks in RavennaHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Why does Word require pixel-perfect accuracy when trying to resize columns/rows? Who thought that was a good idea?
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