# Causal Formalism and RCTs

**URL:** <https://discourse.datamethods.org/t/causal-formalism-and-rcts/28854>\
**Category:** causal inference\
**Tags:** interpretation, design\
**Created:** [September 10, 2026, 2:33pm UTC](https://discourse.datamethods.org/t/causal-formalism-and-rcts/28854 "2026-09-10T14:33:46Z")\
**Posts on this page:** 1\
**Showing post:** 13

<div class="post-metadata">

**Author:** ![ESMD](https://discourse.datamethods.org/letter_avatar_proxy/v4/letter/e/9e8a1a/32.png) [@ESMD](https://discourse.datamethods.org/u/ESMD)\
**Post date:** [September 13, 2026, 10:20pm UTC](https://discourse.datamethods.org/t/causal-formalism-and-rcts/28854/13 "2026-09-13T22:20:24Z")

</div>

Acceptance/non-acceptance of the potential outcomes framework aside, is there at least consensus that causal diagrams can be helpful in the design of RCTs in more complex therapeutic areas? I’m thinking, specifically, about @Pavlos_Msaouel’s point in [this post](https://discourse.datamethods.org/t/individual-response/5191/194). He has found that constructing causal diagrams in the design phase of oncology RCTs is helpful in anticipating the type of covariate information that will be important to collect at various transition times, for cancer therapies that are given sequentially. Is there any reason to dispute the _necessity_ of constructing causal diagrams in anticipation of developing “state transition models” in this particular context?

---

_[View the full topic](https://discourse.datamethods.org/t/causal-formalism-and-rcts/28854)._