, 7 tweets, 3 min read Read on Twitter
Randomization never ensures zero #confounding bias. It provides probabilistic bounds on confounding.

Therefore, by bad luck, the effect estimates from some perfectly conducted randomized #trials are substantially confounded. But we don't know which ones!

An eye-opening example:
In Denmark, 860 individuals were randomly allocated to either "intervention" or "control":
• No intervention was implemented
• Individuals were unaware of their allocation
• Mortality was higher in the intervention group with p=0.003

Keep this in mind when evaluating a trial.
Vass M (PhD Thesis). Prevention of functional decline in older people. Faculty of Health Sciences, University of Copenhagen 2010, p.120.

Thanks to Mikkel Zöllner Ankarfeldt for bringing this example to my attention.
One explanation of this result is “bad luck”. Everybody knows that at least 5% of perfect #trials in the best journals are wrong—its 95% confidence interval doesn't include the true value.

But attributing the result to “bad luck”—and stopping there—misses an important point.
“Bad luck” means that some prognostic factors happened to be more common in the intervention group.

In observational studies, we call this imbalance confounding.

In randomized trials, the imbalance occurs by chance so we can call it "random confounding."
Thinking of bad luck as random confounding is helpful because confounding, whether random or not, can be reduced via adjustment for measured covariates.

That is, in randomized trials, we are better off ADJUSTING for prognostic factors that happen to be imbalanced between groups.
Yes, the Danish result is due to chance, but we are not completely helpless against chance: We could adjust for imbalanced covariates. Whether the study is observational or randomized is irrelevant.

More details in Chapter 10 of our Causal Inference book: hsph.harvard.edu/miguel-hernan/…
Missing some Tweet in this thread?
You can try to force a refresh.

Like this thread? Get email updates or save it to PDF!

Subscribe to Miguel Hernán
Profile picture

Get real-time email alerts when new unrolls are available from this author!

This content may be removed anytime!

Twitter may remove this content at anytime, convert it as a PDF, save and print for later use!

Try unrolling a thread yourself!

how to unroll video

1) Follow Thread Reader App on Twitter so you can easily mention us!

2) Go to a Twitter thread (series of Tweets by the same owner) and mention us with a keyword "unroll" @threadreaderapp unroll

You can practice here first or read more on our help page!

Follow Us on Twitter!

Did Thread Reader help you today?

Support us! We are indie developers!

This site is made by just three indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3.00/month or $30.00/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!