Topic summary

Absence of evidence and evidence of absence

Research Methods › Statistics effect size worked example number needed to treat

This is a generated summary. It shows the 5 most-liked posts from a topic of 21, in their original order, with the accepted answer included where one exists. It is a reading aid and it will miss nuance — the full topic is the record.

k.roosTL225 Sep 2025#1

Absence of evidence and evidence of absence Writing it up because I had to work it out twice and would rather nobody else did.

Asking about absence of evidence on behalf of the question I keep seeing asked badly, including by me.

Framed properly it is answerable. Framed the usual way it is not, and that is most of why the previous threads went nowhere.

43 likes 10mo

h.friskTL211 Nov 2025#5

The most useful thing anyone has posted about absence of evidence in this category was a table of what had been measured and by whom. That is what I would want again.

17 likes 9mo

g.pemberton_ukTL3Regional · UK7 Dec 2025#8

Absence of evidence and evidence of absence: if a study is small and finds no effect, that is absence of evidence, not evidence of absence. A larger study might find an effect that a small study missed.

It is one reading of the data and not the only reasonable one.

32 likes 8mo

BuchholzTL2Member7 Jan 2026 · edited#12

t.vasquez, post #10: Absence of evidence is worth one more sentence than it usually gets, and the sentence is the one about how the number was arrived at. Go to post

Post #8 and I disagree about the size of the effect, not about the direction.

Confounding: a third variable explains an apparent association. In randomised data, randomisation balances confounders. In observational data, confounders can be adjusted for but unknown ones cannot.

30 likes in reply to #10 7mo

MakinenTL2Member5 Feb 2026#16

s.radich, post #15: Building on post #14 rather than restating it. Time-to-event analysis handles differing follow-up in a way a simple proportion cannot, which is why event rates and Kaplan-Meier estimates can differ. Go to post

Post #12 put the caveat in the right place and I want to underline it.

Absence of evidence is a question about a distribution, not about a value, and treating it as a value is what produces the confident wrong answers.

22 likes in reply to #15 6mo

Read the full topic (21 posts)

This topic was referenced in

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