Biostatistics for clinical researchers

Gold-standard biostatistics —
without writing a single line of code.

MaiStat Research is a statistical analysis suite for clinical researchers — built so that gold-standard biostatistics doesn't require writing a single line of code.

Zero data retention

Your dataset is processed only for your active session and permanently discarded when the session ends — never written to a database, 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 and never used to train a model — and because the engine is transparent, every recommendation is traceable to your study design, not a black-box prediction.

How it's organised

The workflow mirrors the scientific method

Plan

Design the study

Study-design routing, effect-measure selection, and sample-size calculation.

Prepare

Curate the data

Import data, assess missingness, and balance observational cohorts.

Analyse

Run the analysis

Descriptive, comparative, diagnostic, survival, longitudinal, and prediction.

Synthesise

Pool the evidence

Meta-analysis, network meta-analysis, and certainty-of-evidence assessment.

What you get

From study design to a publication-ready protocol

Sample-size calculators

From two means to cluster RCTs, non-inferiority, equivalence, diagnostic accuracy and more.

20+

Reviewer checks

Lancet-grade methodological flags mapped to CONSORT, STROBE, PRISMA, STARD and TRIPOD.

★

Publication-ready tables

APA / NEJM-formatted Table 1, results tables and Summary-of-Findings, exported to Word & PDF.

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R & Python reproducibility code

Every analysis ships with runnable code so a reviewer can reproduce the result independently.

Figures

Publication-ready figures, generated by MaiStat

Every figure below was produced by MaiStat from its built-in synthetic datasets — the same output you get on your own data.

Comparative

Box-and-whisker plots

Group comparisons with medians, quartiles and outliers — alongside the assumption checks and the exact test MaiStat routes you to.

Box-and-whisker plot generated by MaiStat

Synthesise

Forest plot (meta-analysis)

RevMan-grade pooled effects with per-study weights, heterogeneity (I², τ²) and a prediction interval.

Meta-analysis forest plot generated by MaiStat

Survival

Kaplan–Meier curves

Time-to-event survival with at-risk tables and the log-rank comparison between groups.

Kaplan-Meier survival curve generated by MaiStat

Diagnostic

ROC curve & AUC

Diagnostic accuracy with the area under the curve and the optimal threshold.

Network meta-analysis

Network graph & league table

Multi-treatment comparisons with the evidence network, ranked effects and SUCRA.

Network meta-analysis graph generated by MaiStat

Deterministic. Private. Clinician-built. Reproducible.

Deterministic engines Zero data retention Built by a clinician R & Python reproducibility

Run analyses on the in-built synthetic datasets, free, after you sign in — explore every module before you bring your own data.

How to cite

Banerjee M. MaiStat Research: a browser-based, AI-free statistical analysis suite for clinical
      researchers. 2026. Available at https://maistatresearch.com

Questions, bugs, or feature requests

Send a note and it goes straight to the team.

Gold-standard biostatistics —without writing a single line of code.