Meta-analysis

Continuous outcome (means / SDs / n)

Continuous-outcome meta-analysis pools per-study means, SDs and group sizes, giving Hedges' g (SMD) by default, with mean difference and log ratio of means also available.

What is Continuous outcome (means / SDs / n)?

When the original studies report mean ± SD with n per arm, the effect size + SE can be computed mechanically — Hedges' g is the standardised mean difference (Cohen's d with a small-sample correction). Pooling SMDs across studies is the standard approach when the original outcomes are on different scales (e.g. several depression-rating instruments).

Mean difference (MD) is the alternative when all studies share the same outcome scale; report MD over SMD whenever possible because MDs are interpretable in the outcome's units.

When should I use Continuous outcome (means / SDs / n)?

RCT meta-analyses with continuous outcomes.
When studies use different rating instruments and SMD is the only common scale.

What data does it need?

Six numeric columns: mean / SD / n for each arm + optional study labels.

What does it report?

Same as meta_iv with the effect size + SE derived internally.

What does it assume?

Independent studies.
Within-study SDs correctly reflect the variability.

How do I interpret the result?

Prefer MD when all studies use the same instrument (more interpretable); SMD when instruments differ. Report Hedges' g rather than Cohen's d for small-sample-corrected estimation.