Topic summary

Immortal time bias in a claims-database study

Evidence › Study critique risk of bias observational data disputed confounding Closed

This is a generated summary. It shows the 5 most-liked posts from a topic of 35, 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.

mi.almeidaTL214 Jul 2025#1

Immortal time bias in a claims-database study — setting out what I have, and where I think it stops being reliable.

Asking about immortal time bias directly, because I have read four threads on it and each answered a slightly different question.

The version I want answered is the narrow one: given the method stated below, is the result within what anyone else has seen? I am not asking what it means yet.

Method, numbers and the two assumptions I am aware of making are below. If the assumptions are wrong that is more useful to me than agreement.

54 likes 12mo

f.wojcikTL21 Aug 2025#11

l.trevino, post #9: Generalisability and validity are separate axes. A trial can be internally impeccable and still tell you nothing about the person asking. That is what I would do. It may not be what is correct. Go to post

Taking post #8 at face value and following it one step further.

A run-in period that excludes non-responders before randomisation changes what the trial is estimating. It is legitimate design and it must be stated in any summary.

The reasoning is more useful than the number, which is why I have shown it.

27 likes in reply to #9 12mo

k.karlsenTL221 Aug 2025#26

mi.almeida, post #1: Immortal time bias in a claims-database study — setting out what I have, and where I think it stops being reliable. Asking about immortal time bias directly, because I have read four threads on it and each answered a slightly different question. The version I want answered is the narrow one: given the method stated below, is the result… Go to post

Taking post #23 at face value and following it one step further.

Immortal time bias has a well-known answer and a correct answer, and the interesting work is establishing that they are the same. Nobody has done that here yet.

28 likes in reply to #1 11mo

FFaulknerTL3Regular24 Aug 2025#29

e.okafor, post #10: The arithmetic in post #7 is right; the assumption feeding it is the part to check. Bias towards the null and bias away from the null: different criticisms have different directions. Differential dropout might bias away from null; conservative statistical analysis might bias toward null. I looked this up rather than remembered it, which… Go to post

Post #28 describes the usual case. This is about the unusual one.

Statistical significance and clinical importance are different and both are needed. A significant difference below the minimal important difference is a real finding of no practical consequence.

The mechanism is plausible, which is not the same as established.

22 likes in reply to #10 11mo

e.adeyemiTL230 Aug 2025#34

m.dalgaard, post #31: Small methodological point on immortal time bias: repeating a measurement is cheap and resolves most of what is being argued about here at no cost to anyone. Go to post

Where I part company with post #32, and it is a narrow parting.

Having read the whole immortal time bias thread before replying: the question in the first post has not actually been answered yet, and three of us have answered a nearby one instead.

30 likes in reply to #31 11mo

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Critiquing an observational claim about a class effect — one year onEvidence › Study critique · 9 replies

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