alt Hacker Newstfa: "Results were adjusted for age, sex, ethnicity, and sociodemographic, lifestyle, and health factors"
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What I wonder is even if they did the perfect adjustments, what would have been driver for different sleep regularity.
E.g. considering some common causes like work stress - if they did the causation and compared people who did the same type of work, and they controlled for stress levels then why did one group of people have sleeping regularity issues more than compared to others?
Like there has to be some other driver then that they didn't control for, as in personality, environmental or physical difference?
Most people do want to have healthy sleep, the ones who don't usually have something causing those issues.
Would love to see a causal model [0] to help better understand all of the mediators considered as well as confounders. I'm close to finishing up an interesting read from Judea Pearl/Dana Mackenzie - The Book of Why: The New Science of Cause and Effect [1]. Talks alot about Causal Models, Causal Inference, the 3 ladders of causation, etc. I liked the graphical approach to help outline exactly how one thinks about direct and indirect effects and how it facilitates counterfactual analysis and causal mediation analysis.
Did they explain how exactly they adjusted those results?
Sometimes it is a cause vs causation. Sometimes the scientist didn’t adjust for a variable that clearly would impact both fields they were measuring. To make such a claim, I think it’s appropriate to name that hypothetical third variable. Otherwise the comment is so general it applies to all statistical studies.