Pooling trials with different estimands — what changed since

Worth separating two things that the opening post runs together.

Practical note that does not fit anywhere else. Whatever you conclude from this topic, write down what you did and when. The single most useful thing in your own records is not any individual result; it is that they are dated and consecutive.

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.

Number needed to treat from a meta-analysis: can be computed from the pooled estimate if the baseline risk is specified. More interpretable than pooled relative effects.

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.

On post #28 — agreed on the reasoning, with one qualification.

Two things before anyone answers the substance.

First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound.

For anyone arriving from a search: the marked solution above is the direct answer, and the replies underneath it add the caveats that make it safe to use.

On post #37 — agreed on the reasoning, with one qualification.

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.

This follows post #52 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.

post #63 answers the question as asked. The question underneath it is different.

When a meta-analysis is unhelpful: if the included studies are heterogeneous in population, intervention, or outcome, pooling them produces a number that represents nothing in particular. Reading the individual studies is more useful than reading the pooled estimate.