Individual participant data pooling is a much stronger design than aggregate pooling and is rare because it requires cooperation rather than a search.
The rule of thumb is fine; the edge cases are where it earns its keep.
Individual participant data pooling is a much stronger design than aggregate pooling and is rare because it requires cooperation rather than a search.
The rule of thumb is fine; the edge cases are where it earns its keep.
Worth separating two things that post #20 runs together.
When trials differ in population, duration and comparator, the pooled estimate answers a question no individual trial asked. That is worth saying before the number is quoted.
I would not lead a decision with this, but I would not ignore it either.
On individual participant data versus aggregate, the part that usually goes wrong is that the question is asked as though it has one answer. It has a range, and the width of the range is the interesting bit.
If you can post the two or three numbers you are working from, several people here will check the arithmetic rather than argue about the conclusion.
Read the full topic (35 posts)
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What pooling buys you and what it destroys
The question in the title: What pooling buys you and what it destroys I will give what I have already checked below so nobody repeats it. The question about pooling buys that I actually want answered is the…
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+74 | 83 | 6.6k | 8mo |
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Coming back to: Reading a meta-analysis you disagree with, fairly
Reading a meta-analysis you disagree with, fairly Writing it up because I had to work it out twice and would rather nobody else did. Reading a meta-analysis — I have the observation and I do not trust my…
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+30 | 34 | 9.3k | 17mo |
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Prediction intervals and why they are more honest than confidence intervals
Posting this under the heading it deserves: Prediction intervals and why they are more honest than confidence intervals Everything below is what sits behind that. I have spent a fortnight trying to pin…
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+21 | 25 | 46k | 4mo |
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Revisiting: What pooling buys you and what it destroys
On the subject in the title: Revisiting: What pooling buys you and what it destroys Working notes rather than a conclusion. Pooling buys — I have the observation and I do not trust my interpretation of it, so…
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+97 | 107 | 4k | 19h |
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About the Meta-analyses category
Pooled estimates, heterogeneity, publication bias, and when pooling was a mistake. This post is a community wiki: any member at trust level 3 or above can edit it, and every edit is recorded with its author…
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4 | 15k | 13mo |
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SURPASS-2 and the comparator dose question that will not go away
SURPASS-2 and the comparator dose question that will not go away — setting out what I have, and where I think it stops being reliable. A methods question rather than a substantive one, about SURPASS-2.…
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+101 | 111 | 1.5k | 18mo |
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Revisiting: Journal club: SURMOUNT-OSA and a hard endpoint in a soft field
Revisiting: Journal club: SURMOUNT-OSA and a hard endpoint in a soft field — setting out what I have, and where I think it stops being reliable. Collecting what is known about SURMOUNT-OSA in one place,…
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+108 | 122 | 52k | 7d |
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About the Meta-analyses category
Pooled estimates, heterogeneity, publication bias, and when pooling was a mistake. This post is a community wiki: any member at trust level 3 or above can edit it, and every edit is recorded with its author…
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4 | 15k | 13mo | |
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Coming back to: Nausea profile of amylin analogues compared with GLP-1 agonists
Posting this under the heading it deserves: Nausea profile of amylin analogues compared with GLP-1 agonists Everything below is what sits behind that. Nausea profile of amylin analogues — I have the…
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+48 | 53 | 31k | 13mo |
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What TRIUMPH is designed to answer, and why we should not pre-empt it — does this still hold?
Asking directly, because I could not find a straight answer: What TRIUMPH is designed to answer, and why we should not pre-empt it — does this still hold? An honest uncertainty about TRIUMPH rather than a…
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+43 | 47 | 5.5k | just now |