{
  "$type": "site.standard.document",
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  "path": "/t/thinking-clearly-about-association-studies-risk-factors-and-causal-salad-included/28679#post_7",
  "publishedAt": "2026-03-29T21:12:02.000Z",
  "site": "https://discourse.datamethods.org",
  "tags": [
    "Initial data analysis"
  ],
  "textContent": "f2harrell:\n\n> Initial data analysis which is blinded to any linkage between X and Y and should proceed both experimental and observational data analysis\n\n  * IDA seems close to Tukey’s EDA. Is this observation correct?\n\n\n\nf2harrell:\n\n>   * Descriptive studies, which deal mainly with characterizing univariate distributions and relationships among Xs using correlation matrices and variable clustering and other unsupervised learning techniques\n>   * Descriptive studies of relationships between individual Xs and Y without prediction or inference\n>\n\n\n  * Am I correct in reading f2harrell’s characterization of descriptive studies as: A descriptive study can hardly include a multivariable model of Y? (exceptions to this clunky rule are granted)\n\n\n\nf2harrell:\n\n> An open question is whether association studies help or hurt the last two steps, i.e., whether empirical association analysis should inform the development of the causal diagram.\n\n  * I agree with ESMD that I find this and the idea of a non-zero association as a “first step” unsettling. If we assume this _might_ be true, again devils advocate, grants this plausible deniability of any scientific confusion? Or in the best case, that association studies are somewhat justifiable?\nDo you happen to have more literature on the view they might be some value in these studies?\n\n",
  "title": "Thinking Clearly about Association Studies (Risk Factors and Causal Salad included)"
}