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  "path": "/t/thinking-clearly-about-association-studies-risk-factors-and-causal-salad-included/28679#post_6",
  "publishedAt": "2026-03-29T21:05:25.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "Thank you all three of you for your input, this is highly appreciated!\nThe papers are now all added to my library\n\ntrumanfrancis:\n\n> Her term for the dominant mode is _seemingly causal_. A specific exposure disease relationship is front and center, but the aims are written as “to examine the independent association between X and Y” or “is X a risk factor for Y?” This isn’t a genuine fourth epistemological category sitting alongside description, prediction, and causation. It’s a rhetorical posture causal intent with the causal accountability stripped out. The authors want you to read the finding causally. They just don’t want to be held to the standards that causal inference requires.\n\nI fully share the sentiment. Playing devils advocate:\nHow would you engage researchers that claim they in fact do not want me to read the finding causally? Let’s exclude malicious intent. In my experience the researchers in question have been brought up in this mode of thinking and are so entrenched in it that they truly _believe_ there is a fourth epistemological category (though they don’t now about the “3 categories” in the first place).\n\nIs the only way out going back to basics and teaching understanding from the ground up to the point where they can understand enough statistics that they see that the practice isn’t logically valid?",
  "title": "Thinking Clearly about Association Studies (Risk Factors and Causal Salad included)"
}