# Decades of underpowered RCT

**URL:** <https://discourse.datamethods.org/t/decades-of-underpowered-rct/28236>\
**Category:** research methods\
**Tags:** rct\
**Created:** [July 2, 2025, 7:05pm UTC](https://discourse.datamethods.org/t/decades-of-underpowered-rct/28236 "2025-07-02T19:05:28Z")\
**Posts on this page:** 1\
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**Author:** ![simongates](https://discourse.datamethods.org/user_avatar/discourse.datamethods.org/simongates/32/367_2.png) [@simongates](https://discourse.datamethods.org/u/simongates)\
**Post date:** [July 3, 2025, 6:24am UTC](https://discourse.datamethods.org/t/decades-of-underpowered-rct/28236/2 "2025-07-03T06:24:19Z")

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Yes, it’s a problem. The traditional way of thinking about trials is that they should be independent and not incorporate information that we already have.

Scott Berry talks about this issue (among others) here

[![](https://discourse.datamethods.org/uploads/default/original/2X/4/48d7ae48eb311ed1ce5ed878534055cc02c4432f.jpeg "A Statistician reads JAMA") ](https://www.youtube.com/watch?v=FFyyJQuA2So&t=2068s)

also this datamethods thread

> [@A Statistician Reads JAMA](https://discourse.datamethods.org/t/a-statistician-reads-jama/28225/5):
>
> You’re right - I should have said “significance testing.”

Scott makes the point that when a 1000 patient trial is suggestive but inconclusive (“fails to show significance”) the usual reaction is to do a 2000 patient trial, rather than add maybe a few hundred to the existing evidence. At best this is a waste of resources.

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