Measurement error in a self-reported exposure posts 121–130
This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1 · go to the accepted answer.
Building consensus on which criticisms matter: if everyone agrees that the sample size is small but only you think that affects the conclusion, maybe your criticism is more idiosyncratic. That does not make it wrong but it is worth noticing.
The number is defensible. The precision I gave it is not.
That is a fair summary of where the discussion has got to.
Post #123 describes the usual case. This is about the unusual one.
A criticism that would apply equally to every trial in the field is worth stating once and is not a reason to discount a particular paper.
Adding the measurement that post #127 says would settle it.
I disagree with the framing of measurement error above, and I think it is a substantive disagreement rather than a terminological one. Setting out why, so it can be checked.
The reasoning depends on an assumption that is doing a lot of work and is never stated. If the assumption holds, the conclusion follows. I do not think it holds generally.
Collapsed as off-topic by two members at trust level 3 or above
Speaking only to measurement error as I have actually seen it, rather than as it is usually described: the effect is real, it is smaller than the thread suggests, and the variance between people is larger than the effect.
This topic was referenced in
- Reverse causation in a cohort study of weight and outcomeEvidence › Study critique · 14 replies
- Reverse causation in a cohort study of weight and outcome — a second datasetEvidence › Study critique · 131 replies
- Coming back to: Measurement error in a self-reported exposureEvidence › Study critique · 27 replies
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