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Meta-Analysis Calculator and Forest Plot

Combine results from several studies into one pooled estimate. Get fixed and DerSimonian-Laird random-effects models, heterogeneity statistics and a publication-ready forest plot.

Free · No sign-upReplaces RevMan · CMAWorks with your data
Updated · By Bibin Xavier

Data 10 × 4

Paste from Excel, or drop a CSV, TSV or Excel file here.
Example data 10 rows, 4 variables. Data stays in this browser tab.
Studytext · 10 levelsEffect_Size_dnumericSEnumericNnumeric
Adams 20150.050.13238
Bose 2016-0.060.2281
Chen 20170.310.12285
Duarte 20180.180.15177
Eriksen 20180.250.13229
Fofanah 20190.750.3141
Gupta 20200.010.2851
Halvorsen 20210.140.297

Variables and options

Results update automatically when you change an option.

Results

10 rows · example data
Pooled effect (random)0.249[0.12, 0.37]
p-value< .001z = 3.86
I²30.3%moderate
τ²0.0121
Table 1

Pooled estimates

ModelEstimateSE95% CIzp
Fixed effect0.2470.052[0.145, 0.349]4.76< .001
Random effects (DL)0.2490.064[0.122, 0.375]3.86< .001

Note. 95% prediction interval: [-0.045, 0.542].

Table 2

Heterogeneity

QdfpI²τ²H²
12.909.16730.3%0.01211.43

Forest plot

StudyEffect and 95% CIEstimate [95% CI]WeightAdams 20150.05 [-0.20, 0.30]14.3%Bose 2016-0.06 [-0.49, 0.37]6.9%Chen 20170.31 [0.07, 0.55]15.7%Duarte 20180.18 [-0.11, 0.47]12.0%Eriksen 20180.25 [0.00, 0.50]14.3%Fofanah 20190.75 [0.14, 1.36]3.8%Gupta 20200.01 [-0.54, 0.56]4.6%Halvorsen 20210.14 [-0.25, 0.53]8.0%Ito 20220.40 [0.05, 0.75]9.3%Jansen 20230.56 [0.25, 0.87]11.0%Random effects model0.25 [0.12, 0.37]100%-0.54-0.060.410.881.36Heterogeneity: Q = 12.90, df = 9, p = .167; I² = 30.3%; τ² = 0.0121

Interpretation

The pooled random-effects estimate is 0.25 (95% CI 0.12 to 0.37) and is statistically significant. Heterogeneity is moderate (I² = 30.3%).

A random-effects meta-analysis of 10 studies gave a pooled effect of 0.25, 95% CI [0.12, 0.37], z = 3.86, p < .001; heterogeneity Q(9) = 12.90, p = .167, I² = 30.3%.

How to cite this tool

Using these results in a thesis, journal article, report or class assignment? Please cite this free tool so others can find it. It keeps the site free.

APA 7

Xavier, B. (2026). Meta-Analysis Calculator and Forest Plot [Web application]. FreeStatisticalTools.com. https://freestatisticaltools.com/meta-analysis-calculator/

BibTeX 

@software{xavier_metaanalysis_2026,
  author = {Xavier, Bibin},
  title = {Meta-Analysis Calculator and Forest Plot},
  publisher = {FreeStatisticalTools.com},
  year = {2026},
  url = {https://freestatisticaltools.com/meta-analysis-calculator/},
  note = {Web application}
}

Suggested sentence for your methods section: “The analysis was carried out with the free Meta-Analysis Calculator and Forest Plot tool on FreeStatisticalTools.com (Xavier, 2026).”

What is meta-analysis?

Meta-analysis combines effect sizes from several studies into one pooled estimate. This calculator fits fixed-effect and random-effects models, quantifies heterogeneity and draws a forest plot.

When to use meta-analysis

Use it to combine effect sizes (Cohen’s d, Hedges’ g, log odds ratios, correlations as Fisher’s z) from studies of the same question.

How to set up your data

One row per study with a label, an effect size, and either its standard error or its 95% confidence limits. Enter ratios (OR, RR, HR) on the log scale and tick the log option.

How to use this tool

  1. Enter your data. Paste columns from Excel, Google Sheets or SPSS with variable names in the first row, or upload a CSV or Excel file. The example data shows the expected layout.
  2. Choose the variables. Select the study label, effect size and standard error.
  3. Set the options. Fill in precision given as, model and effects are log ratios (show as or/rr).
  4. Read the results. Results update automatically. Read the plain-English interpretation, then use Copy table to paste APA-style tables into Word and Copy for the results sentence.

How to report meta-analysis in APA style

Report the model, the pooled estimate with its CI, Q, I² and τ², and include the forest plot.

Frequently asked questions

Fixed or random effects?

Use random effects when studies differ in populations or methods, which is usual. Fixed effect assumes one true effect shared by all studies.

How do I interpret I²?

I² is the percentage of variability due to real differences between studies: about 25% low, 50% moderate and 75% high (Higgins et al., 2003).

Can I enter odds ratios?

Yes. Enter log odds ratios with their standard errors or confidence limits on the log scale, and tick the log option to show results as ratios.

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