{
  "$type": "site.standard.document",
  "bskyPostRef": {
    "cid": "bafyreifycmqoar2gcczh7ej3x226rh2m5duuewjdidcvojkyf6wj2c3rsa",
    "uri": "at://did:plc:wwyqal4cnqhuwyacdj7rqq3n/app.bsky.feed.post/3miaqtdzserk2"
  },
  "path": "/t/thinking-clearly-about-association-studies-risk-factors-and-causal-salad-included/28679#post_9",
  "publishedAt": "2026-03-30T01:24:19.000Z",
  "site": "https://discourse.datamethods.org",
  "textContent": "trumanfrancis:\n\n> 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\nAgree. My collaborators frequently point out that I should use precise language, not vague language. I often lack confidence, so this must be my problem. Then, when I use causal language, they criticize me harshly, saying it’s observational research, you shouldn’t use causal language!\n\nESMD:\n\n> This incentive misalignment does not reflect personal failure on the part of the researcher, but rather a corrupted research ecosystem.\n\nAbout three years ago, I strengthened the adjustment for confounding factors in an analysis and reportred that the results was no statistically significant. My boss pointed out that no top journal would accept an article without statistical significance (I donnot think so).\nI insisted on not making any revision and showed the reasons. And even without enough adjustments, the lower limit of the 95% confidence interval was 1.00. He then threatened to withdraw data support if I made the adjustments. Finally, I quit from the project.",
  "title": "Thinking Clearly about Association Studies (Risk Factors and Causal Salad included)"
}