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  1. I’ve been trying to read more carefully about instrumental variables and make up my mind about when IV arguments are scientifically convincing.

    Here's a tension I keep running into:

    Should the scientific question alone determine the causal parameter of interest?

    Or is it legitimate for the target parameter to reflect an interplay between scientific interest and the identifying assumptions we actually find tenable?

    IVs can be difficult to interpret when instruments are weak, who “compliers” are is opaque, exclusion restrictions are debatable, or linear models are used in settings where the true data-generating process may be nonlinear.

    On the other hand, when an entire body of (aspirationally causal) literature rests on methods that try to close backdoor paths, IVs offer a genuinely different identification strategy. That seems valuable for evidence triangulation, even if IV analyses have their criticisms.

    What do you think? Are you a big IV proponent? Are you an IV critic?

    When do you find IV evidence persuasive?

    Some literature I've been reading & re-reading:

    pubmed.ncbi.nlm.nih.gov/167552

    academic.oup.com/ije/article/4

    pmc.ncbi.nlm.nih.gov/articles/

    arxiv.org/abs/2402.09332

    arxiv.org/abs/2402.05639

    #CausalInference #InstrumentalVariables #Econometrics #Statistics #DataScience #HealthPolicy

  2. On FTL and causality: add new time. Light vortices look a lot like a light cone on a time-space diagram to me.

    Do photons have spin...? Long Covid sucks.

    While we all live in a money-obsessed hellscape, nothing needs "utility" to be worth testing or knowing.

    youtube.com/watch?v=E1RVRB9X3H0

    #Summary #Precis #Abstract #Physics #Microscopy #Light #EM #Fields #ParticlePhysics #Energy #science #ScienceMastodon #ScientificMethods #learning #testing #experiments #experimentation #LightVortices #LightVortex #CausalInference #Causality #IDFK

  3. But yeah, I am confused about the polaritons. 
    (Polaritrons? I'm not hearing stuff / processing audio precisely, lately. ) Light has a shape? Or, like, a shape in time? Cuz that -3, -2, -1, 0, +1, +2, +3 image looks a lot like a light cone on a time-space diagram. To me, at least. The things with the light at diagonal lines in space.

    Wait. Spin? Do photons have spin? I'm gonna get a used copy of my uni textbook off someone and try to remember anything. Yaaay Long Covid! (Twice, Doubled, or Squared! Per your preference.)

    youtube.com/watch?v=E1RVRB9X3H0

    #Physics #Microscopy #Light #EM #Fields #ParticlePhysics #Energy #science #ScienceMastodon #ScientificMethods #learning #testing #experiments #experimentation #LightVortices #LightVortex #CausalInference #Causality #IDFK

  4. On how faster-than-light info would affect (our understanding of) causality: "And then nothing makes sense anymore." Since when has science stopped testing things that seemed "unintuitive" on the first pass? 
    Wouldn't that just sort itself out, and then we'd make new inferences to test? Cuz it sounds like an additional dimension of time would be useful here. Which... is probably a meme. "Just add a new dimension!" Ok yeah, but what if we did tho. (Eddie Woo intensifies.)

    youtube.com/watch?v=E1RVRB9X3H0

    #Physics #Microscopy #Light #EM #Fields #ParticlePhysics #Energy #science #ScienceMastodon #ScientificMethods #learning #testing #experiments #experimentation #LightVortices #LightVortex #CausalInference #Causality #IDFK

  5. New study uses causal analysis to demonstrate big reductions in carbon emissions if fewer bovines.
    In ten years, methane emissions from all activities if bovine stop would be 80 % of methane emissions from all activities if no intervention.
    Results and causation are presented at doi.org/10.5281/zenodo.19019693

    #carbon #causality #causalInference #causation #confounding #counterFactuals #emissions #GHG #methane #offPolicy #policy #publicPolicy

  6. "Five skills. Each one is counter-cyclical (becomes more valuable as hype recedes), resistant to LLM automation (requires human judgment that pattern-matching can’t replicate), and directly tied to the business outcomes executives actually pay for."
    by Kaushik Rajan: towardsdatascience.com/the-ai-

    #DataScience #BayesianStatistics #BayesianStats #Bayesian #causalInference #experimentalDesign #SPC #statisticalProcessControl

  7. Surprising result, nice study design

    When "Likes" went private on X there was no detectable change in the number of Likes received on posts by "high reputational risk" accounts

    arxiv.org/pdf/2601.11140

    #CausalInference #DifferenceInDifference #SocialMedia #Research