How to read a forest plot, properly, from scratch

Adding the measurement that post #13 says would settle it.

Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers.

Scoping that to what I have actually seen rather than what I have read.

Absolute numbers, not just relative: a 30% relative reduction tells you the ratio but not the practical magnitude. The event rate in each arm and the difference between them tells you how many people benefit.

Second-hand, so weight it accordingly.

A treatment-policy estimand asks what happens to people assigned to a strategy, including those who abandon it. A hypothetical estimand asks what would have happened had everyone continued. Both are legitimate and they give different numbers.

The arithmetic in post #16 is right; the assumption feeding it is the part to check.

Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers.

Adding a source would improve this post and I do not have one to hand.

Answering the question post #18 raises rather than the one it answers.

Absolute numbers, not just relative: a 30% relative reduction tells you the ratio but not the practical magnitude. The event rate in each arm and the difference between them tells you how many people benefit.

Not the answer, but possibly the question that gets there.

Risk of bias: structured appraisal of internal validity. Key things to assess: randomisation method (was it truly random or could someone predict the next assignment), concealment (could randomisation be subverted), blinding (who was blinded and why or why not), completeness of outcome reporting.

For what it is worth, the same held on the two occasions I checked.

Sensible. I would want the same detail before I acted on it either.

Everything in post #19 holds. The case it does not cover is the one I have.

A treatment-policy estimand asks what happens to people assigned to a strategy, including those who abandon it. A hypothetical estimand asks what would have happened had everyone continued. Both are legitimate and they give different numbers.

The arithmetic in post #23 is right; the assumption feeding it is the part to check.

Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers.

Post #23 and I disagree about the size of the effect, not about the direction.

Absolute numbers, not just relative: a 30% relative reduction tells you the ratio but not the practical magnitude. The event rate in each arm and the difference between them tells you how many people benefit.

Absolute and relative effects answer different questions. Write down the event rate in each arm and the difference between them; everything quotable is derived from those two numbers.

A guess, clearly labelled as one.

A treatment-policy estimand asks what happens to people assigned to a strategy, including those who abandon it. A hypothetical estimand asks what would have happened had everyone continued. Both are legitimate and they give different numbers.

I would hold that lightly until someone with a larger sample weighs in.

Narrowing post #27, because the general version has more than one answer.

Risk of bias: structured appraisal of internal validity. Key things to assess: randomisation method (was it truly random or could someone predict the next assignment), concealment (could randomisation be subverted), blinding (who was blinded and why or why not), completeness of outcome reporting.

Clear enough that I do not think I have a follow-up, which is unusual.

Post #27 is the version of this I will quote in future. One addition.

Discontinuation handling is the methodological detail that most changes a result and gets the least attention. Read how missing data was imputed before reading the effect size.