Topic summary

A pooled estimate that changed when one trial was added

Evidence › Meta-analyses meta-analysis publication bias effect size Solved

This is a generated summary. It shows the 5 most-liked posts from a topic of 29, 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.

il.dumitruTL2 Moderator22 May 2026#2

This follows the opening post rather than contradicting it.

Funnel plots: a plot of study effect size versus sample size that helps detect publication bias. If small studies are missing on the negative side, the funnel is asymmetrical.

27 likes 2mo

n.zielinskiTL2 Moderator Solution10 Jun 2026#8

i.osei, post #4: Fixed-effects versus random-effects models: fixed-effects assumes all studies are estimating the same thing and variation is sampling error. Random-effects assumes studies are estimating effects from different distributions and allows between-study variance. Choice matters if heterogeneity is high. Go to post

I disagree with the reply above, and I think the disagreement is substantive rather than terminological.

The distinction being drawn does not survive when you look at the published data for this specific question. I would be glad to be shown wrong on this, because the version I am arguing against is more convenient.

8 likes in reply to #4 2mo

r.villalobosTL2 Moderator20 Jun 2026#12

I read post #10 twice before replying, because I had assumed the opposite.

Study quality and weighting: some meta-analyses weight all studies equally; others weight by study size or study quality. The choice affects the result and should be stated and justified.

28 likes 1mo

r.aldana_pharmdTL4Pharmacist6 Jul 2026#19

Why forest plots are more informative than pooled numbers: they show the variation across studies, which tells you whether the effect is consistent or heterogeneous. A narrow confidence interval around a meaningless centre is less useful than a wider interval that shows real differences.

27 likes 22d

z.okonkwoTL2 Moderator24 Jul 2026#28

s.balogun, post #24: Fixed-effects versus random-effects models: fixed-effects assumes all studies are estimating the same thing and variation is sampling error. Random-effects assumes studies are estimating effects from different distributions and allows between-study variance. Choice matters if heterogeneity is high. Go to post

Thank you for the correction. I have edited my earlier post with a note rather than silently, so the thread still makes sense to read. The error was mine and it was the kind that comes from remembering a figure instead of looking it up.

30 likes in reply to #24 4d

Read the full topic (29 posts)

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