Combine several study effects into one pooled estimate with honest maths.
What this tool does
This tool pools the effects from several studies into a single estimate using fixed-effect inverse-variance maths. You enter one study per line with its effect size and standard error, and the tool weights each study by the inverse of its variance, so more precise studies count more, then reports the pooled effect with a 95 percent confidence interval and each study’s weight. The maths is the standard fixed-effect recipe, shown openly in the results table.
It works fully in your browser. Nothing is uploaded to a server, and you do not need an account. Paste your text, press the button, and read the result on the same page. That makes it useful for students, researchers, and anyone who has to get through a long paper quickly without losing the important parts.
How to use it
List each study on its own line in the format study name, vertical bar, effect size, vertical bar, standard error. Press the pool button and read the pooled effect and interval first, then the weights table to see which study dominates. If one study carries more than half the weight, your pooled result is mostly that one study, whatever the average says.
Worked example
Three studies with effects 0.45, 0.30, and 0.55 and standard errors 0.12, 0.10, and 0.15 pool to about 0.41 with a 95 percent interval roughly from 0.24 to 0.58. The middle study, with the smallest standard error, carries the largest weight, near 40 percent, while the least precise study carries the least. The interval excludes zero, but that alone does not prove the effect matters in practice.
How to read the results
The output gives the pooled effect and its 95 percent confidence interval in large text, followed by a table of studies with effects, standard errors, and percentage weights. Weights sum to 100 percent, so you can audit the calculation: a study with half the standard error gets roughly four times the weight, because weight uses the inverse squared error.
Do not treat the output as a final answer. It is a starting point for your own reading. Skim the highlighted parts first, then read the full passage around anything that matters for your work. A tool can point at the likely important sentences, but only you can judge whether they are actually important for your question.
Honest limits
Fixed-effect pooling assumes every study estimates one single true effect, which is often false when populations, measures, or settings differ. It does not test heterogeneity, does not adjust for publication bias, and does not replace a full meta-analysis with random effects, forest plots, and sensitivity checks. Use it for teaching and quick checks, and run a proper analysis before publishing any pooled claim.
This tool does not use artificial intelligence, and it does not understand your paper the way a human reader does. It follows fixed rules that you can inspect in the results. That is a strength when you want transparent, repeatable results, and a weakness when a passage needs real understanding, context, or judgement.
Tips for best results
Paste clean text. Remove page headers, footers, and reference lists before you paste, because they add noise to word counts and sentence scores. Work on one section at a time for long papers, and keep your original file open beside the tool so you can check anything surprising against the source. If you use the result in your own writing, always cite the original paper, never the tool output.
Frequently asked questions
Is it free? Yes. The tool is free to use online, with no sign-up and no download.
Is my text stored anywhere? No. Everything runs in your browser tab. Closing the tab removes your pasted text.
Can I trust the output completely? No tool of this kind should be trusted blindly. Use it to speed up reading and checking, then verify the important claims yourself in the original text.
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Versión en español: Herramienta de Agrupación de Metaanálisis · All Free Online Tools.
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