02 / 07 · Meta-Analysis

Meta-Analysis Services

Advanced Statistical Pooling with Publication-Ready Forest Plots

A meta-analysis transforms pooled data from multiple independent studies into a single, statistically powerful conclusion. When conducted with methodological precision — correct model selection, heterogeneity analysis, subgroup testing, and publication bias assessment — it provides the highest level of quantitative evidence in clinical research. Our meta-analysis services deliver publication-ready outputs built to withstand the most rigorous peer review.

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Meta-Analysis

Advanced Statistical Pooling with Publication-Ready Forest Plots

29+RCTs in Largest NMA

61Most Reviewer Comments Handled

Q1Target Journal Tier

RevMan 5Stata (metan, metareg)R (meta, metafor, netmeta)OpenMeta[Analyst]GeMTC (NMA)JASPGRADEpro

Free Consultation

Response within 24 hours

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What Is It?

Understanding Meta-Analysis

A meta-analysis is a statistical technique used within a systematic review to quantitatively combine results from multiple studies addressing the same research question. It produces a single pooled effect estimate (odds ratio, risk ratio, mean difference, or hazard ratio) with 95% confidence intervals, representing a more precise estimate than any individual study alone.

Not all systematic reviews include a meta-analysis — statistical pooling is only appropriate when included studies are sufficiently homogeneous in population, intervention, comparator, and outcome. Our meta-analysis services include a full assessment of pooling appropriateness before any analysis begins.

Why It Matters for Publication

Required by Q1 journals including The Lancet, JAMA, and BMJ

Peer reviewers assess methodology quality before evaluating science

Methodological rigour directly determines acceptance probability

MD. Massab Bashir has supported 20+ Q1 publications

97%

Job Success Score on Upwork

What's Included

Every Deliverable — Documented

No vague promises. Every engagement specifies exactly what you receive, at what standard, by what deadline.

Effect Size Calculation

Computation of odds ratios, risk ratios, mean differences, standardised mean differences, or hazard ratios with 95% confidence intervals for each included study.

Model Selection (Fixed vs Random Effects)

Evidence-based selection between fixed-effect (Mantel-Haenszel, inverse-variance) and random-effects (DerSimonian-Laird, REML) models with full justification.

Heterogeneity Analysis

I² statistic, Cochran's Q test, and tau² estimation with clinical and statistical interpretation of between-study variability.

Subgroup & Sensitivity Analyses

Pre-specified subgroup analyses by population, intervention dose, follow-up duration, study quality, and setting. Leave-one-out sensitivity analyses to assess result robustness.

Publication Bias Assessment

Funnel plot construction, Egger's regression test, Begg's rank correlation, and trim-and-fill analysis where indicated.

Network Meta-Analysis (NMA)

Indirect treatment comparisons for multiple interventions — network geometry plots, SUCRA ranking, league tables, consistency testing using frequentist or Bayesian frameworks.

Publication-Quality Forest Plots

Professionally formatted forest plots, funnel plots, network plots, bubble plots, and GRADE summary of findings tables — ready for direct journal submission.

Statistical Code & Reporting

Full statistical analysis code (RevMan, Stata, R) provided with the manuscript for transparency and reproducibility.

Tools & Methodologies

RevMan 5Stata (metan, metareg)R (meta, metafor, netmeta)OpenMeta[Analyst]GeMTC (NMA)JASPGRADEpro

Who This Is For

PhD students and early-career researchers

Clinicians and medical consultants

University research departments

Hospital-based research teams

Healthcare organisations and NGOs

Researchers targeting Q1 journal publication

The Process

How We Work Together

Transparent, structured engagement from first contact to final delivery — with clear milestones and no surprises.

Data Assessment

Review your extracted data for pooling appropriateness, outcome definitions, and statistical compatibility.

Model Selection

Select the correct statistical model based on study design, data type, and clinical heterogeneity.

Primary Analysis

Conduct pooled meta-analysis, calculate effect sizes, and assess heterogeneity.

Sensitivity Analyses

Run pre-specified subgroup and sensitivity analyses to test robustness of primary results.

Publication Bias

Funnel plot, Egger's test, and trim-and-fill analysis for publication bias.

Figures & Manuscript

Forest plots, GRADE tables, and full statistical reporting section for manuscript.

About Your Consultant

MD. Massab Bashir

Medical Physician · PhD Researcher · Top Rated Plus

🎓Medical Physician with clinical foundation in evidence-based practice

🔬PhD Researcher in Immunology — advanced research methodology

⭐Top Rated Plus on Upwork — 97% Job Success Score

📄20+ Q1 publications supported

Free 30-Minute Consultation

Discuss your project and receive an accurate quote at no cost.

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FAQ

Frequently Asked Questions About Meta-Analysis

What types of meta-analysis do you conduct?+

We conduct pairwise meta-analysis (comparing two interventions directly), network meta-analysis (NMA) for multiple treatment comparisons, dose-response meta-analysis using restricted cubic splines, individual patient data (IPD) meta-analysis support, and diagnostic meta-analysis using bivariate and HSROC models.

Which software do you use for meta-analysis?+

We use RevMan 5 for standard pairwise meta-analysis (the Cochrane standard), Stata (metan, metareg packages) for advanced analyses and publication bias tests, and R (meta, metafor, netmeta packages) for network meta-analysis, dose-response analysis, and complex models. All code is provided with the manuscript.

What is network meta-analysis and when is it needed?+

Network meta-analysis (NMA) allows indirect comparison of treatments that have not been compared head-to-head in RCTs. It is used when multiple interventions exist for a condition and you need to rank them by efficacy or safety. NMA requires a connected treatment network and assumes transitivity — we assess both before conducting any analysis.

How do you handle high heterogeneity (high I²)?+

High I² (>50-75%) does not automatically invalidate a meta-analysis but requires careful interpretation and exploration. We investigate heterogeneity sources through pre-specified subgroup analyses (by population, intervention, setting, study design), meta-regression, and sensitivity analyses. We report heterogeneity transparently and calibrate GRADE certainty accordingly.

Do you provide the forest plots and figures?+

Yes. All meta-analysis outputs include publication-quality forest plots, funnel plots, network plots (for NMA), and GRADE summary of findings tables. Figures are provided in high-resolution formats (TIFF/PDF) ready for journal submission. We format all figures to the specific requirements of your target journal.

Can you conduct a meta-analysis on existing data I have already collected?+

Yes. If you have already completed the screening and data extraction, we can conduct the statistical meta-analysis, produce all figures, interpret the results, and write the Results and Discussion sections of your manuscript. This is one of our most common service configurations for researchers who need statistical expertise.

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