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Stating the estimand of interest can help reduce confusion about what is being estimated, but it is often difficult to determine what is and is not identifiable given a trial\u2019s specific imperfections. We demonstrate how directed acyclic graphs can be used to elucidate the consequences of common imperfections, such as noncompliance, unblinding, and drop-out, for the identification of the intention-to-treat effect, the total treatment effect and the physiological treatment effect. We assert that the physiological treatment effect is not identifiable outside a trial with perfect compliance and no dropout, where blinding is perfectly maintained.<\/jats:p>","DOI":"10.1007\/s10654-025-01298-7","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T03:20:20Z","timestamp":1757560820000},"page":"697-707","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Elucidating some common biases in randomized controlled trials using directed acyclic graphs"],"prefix":"10.1007","volume":"41","author":[{"given":"Erin E.","family":"Gabriel","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alex","family":"Ocampo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arvid","family":"Sj\u00f6lander","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"1298_CR1","unstructured":"Human Medicinal\u00a0Products EMEA. 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