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Meta-analysis

A meta-analysis is not producing a forest plot. The pooled estimate is only useful if the question, studies, outcomes, effect measures, assumptions and interpretation are appropriate.

PRISMA screening flowRecords narrowing through four stages: identification, screening, eligibility, and the studies finally included.
PRISMA screening flow

What you receive

  • Effect-size preparation and harmonisation

  • Forest and funnel plots

  • Heterogeneity, subgroup and sensitivity analyses

  • Reproducible R or Stata analysis where applicable

  • Methods and results text

  • Responses to statistical reviewer comments

How it works

  1. 01

    Should this be pooled?

    Clinical heterogeneity, outcome definitions, follow-up, intervention differences and risk of bias all affect whether a pooled estimate means anything. Sometimes the strongest decision is not to pool.

  2. 02

    Effect measures and model

    Effect-measure selection, data preparation, and fixed-effect or random-effects specification chosen for the evidence rather than by habit.

  3. 03

    Heterogeneity and robustness

    Heterogeneity assessment, subgroup analysis, sensitivity analysis, meta-regression where appropriate, and publication-bias assessment.

  4. 04

    Interpretation

    A pooled estimate should not be presented as stronger than the studies behind it. Results are read in the context of quality, consistency, precision, directness and clinical meaning.

Who this is for

  • Reviewers with extracted data who need the synthesis done properly
  • Researchers unsure whether their evidence should be pooled at all
  • Authors facing statistical reviewer comments on a submitted meta-analysis

What you need to provide

  • The research question and included studies
  • Extracted outcome data, or the extraction sheet as it stands
  • The outcomes you intend to pool

Frequently asked questions

Can you analyse data I have already extracted?

Yes. We review the extraction structure, identify what is missing, and run the analysis if the data support it.

Can you help with statistical reviewer comments?

Yes. We clarify the method, run appropriate additional analyses, and draft transparent responses.

Related reading

  1. 01Publication bias: funnel plots, Egger's test and what they can and cannot showFunnel plot asymmetry has several explanations and publication bias is only one of them. Reading it as proof of missing studies is a common and consequential error.
  2. 02What is heterogeneity in meta-analysis, and what does I² actually mean?I² is widely reported and widely misread. It does not measure how different the studies are, and it is not a threshold for whether pooling is allowed.
  3. 03Fixed-effect vs random-effects meta-analysisThe two models answer different questions. Choosing between them by which one gives a narrower interval is choosing the answer before asking the question.

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