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Statistical Engine

MedStat Guide™

Clinical Statistics You Can Defend

A clinician-grade modelling and calculation engine that runs fully offline, validates assumptions before modelling, and generates publication-ready outputs with transparent mathematics. Every run produces a receipt.

Offline-firstDeterministicAudit-readyMode-B compatible
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100%
Offline-first
0
Assumption violations pass unnoticed
1
Audit receipt per run
APA
Publication-ready outputs
Capabilities

What MedStat Guide™ can do.

01
Modelling Engine
Regression (Linear, Logistic, Poisson), Survival analysis (Kaplan-Meier, Cox), ANOVA/ANCOVA, SEM/CFA, and ML classification — all offline, all deterministic.
LinearLogisticCoxANOVA
02
Sample Size & Power
Deterministic design safety — means, proportions, ANOVA, survival, regression EPV checks, and ML adequacy warnings — with power curves generated automatically.
EPV checksPower curvesML adequacy
03
Diagnostics & Assumptions
Normality, homogeneity, VIF, separation, overdispersion, and proportional hazards checks — with traffic-light indicators before every model run.
NormalityVIFPH check
04
Publication Outputs
APA/Vancouver-formatted tables, equations, and interpretation memos — reviewer-ready from every analysis run with full audit receipts.
APA formatAudit receiptReviewer-ready
Workflow

How it works.

01
Define Study Design
Clinician defines the research question and study parameters. MedStat validates the design feasibility and sample size requirements before proceeding.
02
Validate Assumptions
Traffic-light diagnostics run automatically. Normality, VIF, proportional hazards — all checked and logged before the model executes.
03
Select Method (with trace)
Rule-based method selection produces a documented trace — not a hidden model. Reviewers can follow every decision step by step.
04
Run & Generate Receipt
Deterministic execution produces outputs. An append-only decision receipt is created automatically — every run reproducible by anyone with the same inputs.
05
Export Publication Package
APA/Vancouver tables, interpretation memo, and audit trace exported in a single publication-ready package.
The Trust Gap

Analytics failures rarely show up as runtime errors.

They show up as silent validity issues: mismatched assumptions, underpowered designs, unstable estimates, and outputs that cannot be reproduced under reviewer scrutiny.

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Traditional Workflows

Assumptions checked informally. Method selection undocumented. Outputs not reproducible if the analyst changes.

MedStat Guide™

Assumption registry validates before every model. Method selection trace documents every decision. Deterministic outputs — same inputs always produce same outputs.

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MedStat Guide™?

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