MaiStat

Biostatistics to accelerate research

Precision biostatistics,
in a no-code interface

A statistical analysis suite for researchers, in two modules. MaiStat Analyse takes a primary study from planning to a publication-ready analysis. MaiStat Synthesis pools trials in pairwise and network meta-analysis. Every figure, table and script is generated for you.

Zero data retention

Your dataset is processed only for your active session and permanently discarded when the session ends. It is never written to a database and never retained.

100% AI-free

Every result comes from deterministic, rule-based statistical engines. Your data is never sent to a third-party AI service. MaiStat aims to make every insight verifiable and traceable back to your original study parameters.

Two modules, one platform: Analyse & Synthesise

Choose the module that matches your study.

MaiStat Analyse

Study design to analysis for primary research.

  • Protocol builder with design-driven effect measures and reviewer-grade methodology flags.
  • 27 sample-size calculators, missing-data handling, propensity-score matching and weighting.
  • Descriptive and inferential statistics, diagnostic accuracy, reliability, survival, mixed and prediction models.
  • Runnable Python and R code with every result.
Launch MaiStat Analyse

MaiStat Synthesis

Pairwise and network meta-analysis for systematic reviews.

  • Four review types: intervention, aetiology or prognostic, diagnostic test accuracy, prevalence.
  • Computation by the R packages meta, metafor, bayesmeta, netmeta and gemtc.
  • Risk of bias carried through to GRADE and CINeMA-style certainty ratings.
  • A self-contained R script, data included, for every analysis.
Launch MaiStat Synthesis

What you get

Results a methods reviewer can audit.

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A reproducibility script for every analysis

MaiStat Synthesis emits self-contained R (data inlined, package versions recorded) that re-runs outside MaiStat. MaiStat Analyse ships Python and R code with every result.

R

Engines of record, named

Every page states which engine computed the number. In Synthesis it is always an R package; the software statement lists the exact versions for your Methods section.

★

Guideline-concordant outputs

PRISMA and PRISMA-NMA structure, GRADE and CINeMA certainty, Summary-of-Findings and publication tables exported to Word.

20+

Reviewer checks and sample size

In Analyse: methodology flags mapped to CONSORT, STROBE, STARD and TRIPOD, and 27 sample-size calculators from two means to cluster trials.

Figures

Publication-ready figures, generated for you.

Every figure below was produced by MaiStat from its built-in demonstration datasets, the same output you get on your own data. Synthesis figures are drawn by the R engine that fitted the model.

MaiStat Analyse

Group comparisons

Compare groups with box, violin, means with 95% CI and other views, each backed by the assumption checks and the exact test MaiStat routes you to.

Box-and-whisker plot generated by MaiStat
Violin plot generated by MaiStat
Grouped bar chart of means with 95% CI generated by MaiStat
MaiStat Synthesis

Pairwise meta-analysis

Pooled effects with per-study weights, heterogeneity (I², τ²) and a prediction interval, plus a funnel plot with small-study-effect diagnostic tests, a trim-and-fill adjusted forest plot, and a meta-regression bubble plot.

Meta-analysis forest plot generated by MaiStat
Funnel plot for publication bias generated by MaiStat
Trim-and-fill adjusted forest plot generated by MaiStat
Meta-regression bubble plot generated by MaiStat
MaiStat Analyse

Survival & competing risks

Kaplan-Meier survival with the log-rank test and competing-risks cumulative incidence with Gray's test, each on a clean journal canvas with a colour-matched patients-at-risk table.

Kaplan-Meier survival curve generated by MaiStat
Cumulative incidence functions generated by MaiStat
Analyse & Synthesis

ROC & summary ROC

Diagnostic accuracy from a single-study ROC with its area under the curve to a risk-of-bias-annotated summary ROC across studies.

ROC curve generated by MaiStat
Summary ROC across studies generated by MaiStat
MaiStat Synthesis

Network meta-analysis

Multi-treatment comparisons of the same thrombolytic network: the evidence graph, the frequentist forest plot with P-scores, the comparison-adjusted funnel plot, and the Bayesian (gemtc) forest plot with SUCRA values. League tables and evidence-certainty ratings are exported as tables alongside the figures.

Network meta-analysis evidence graph generated by MaiStat
Frequentist network meta-analysis forest plot with P-scores generated by MaiStat
Comparison-adjusted funnel plot generated by MaiStat
Bayesian network meta-analysis forest plot with SUCRA values generated by MaiStat

Validated • Guided • Reproducible • Private

Validated open-source engines Step-by-step guidance Reproducibility script per analysis Zero data retention No AI in any computation

How to cite

MaiStat Synthesis

Banerjee M, Dutta S. MaiStat Synthesis: a no-code, reproducible pairwise and network meta-analysis module built on validated R engines. 2026. Available at https://maistatresearch.com.

MaiStat Research

Banerjee M. MaiStat Research: a no-code statistical analysis suite for clinical research, version 2.0. 2026. Available at https://maistatresearch.com.

Questions, bugs, or feature requests

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