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duke_notes [2025/11/17 20:34] – [Cochran-Mantel_haenszel test] adminduke_notes [2025/11/17 21:46] (current) admin
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 [[https://stats.libretexts.org/Bookshelves/Introductory_Statistics/OpenIntro_Statistics_(Diez_et_al)./06%3A_Inference_for_Categorical_Data | Inference for Categorical Variables]] [[https://stats.libretexts.org/Bookshelves/Introductory_Statistics/OpenIntro_Statistics_(Diez_et_al)./06%3A_Inference_for_Categorical_Data | Inference for Categorical Variables]]
 +
 +===== General Tips =====
 +
 +  * if you can, pick a continuous outcome over a binary outcome
 +    * Why? For a binary outcome, you'll need a much larger sample size. Continuous outcomes also allow more precision.
 +  * logistic regressions stink!
 +
 +logistic regression = linear model for the log-odds of the outcome
 +
 +=== analyzing relationship between categorical outcome and a continuous covariate ===
 +
 +===effect modification vs confounding===
 +
 +if we don't take effect modification into account, we get an over-generalized estimate of the relationship between the outcome and the exposure for the entire co-hort
 +
 +  * Breslow-Day Test examines if evidence of a differential association between two variables across the level of a third variable
 +    * similar limitations to Cochran-Mantel-Haenszel test
  
 ==== Cochran-Mantel_haenszel test ==== ==== Cochran-Mantel_haenszel test ====
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