Pro Tier Module

Clinical Trial Sample Size & Power Calculator

Two-arm trial sample size and power - superiority, non-inferiority, and equivalence, exact and client-side.

See it run - a worked example, 100% in this browser tab

The problem

Designing a two-arm parallel-group trial means picking the right normal-approximation formula for superiority, non-inferiority, or equivalence and feeding it the correct alpha tail, variance assumption, and margin - small errors quietly mis-size a study.

The local-first solution

This plugin evaluates the cited closed-form sample-size and power equations with a high-accuracy inverse-normal quantile entirely in your browser, echoing every z-quantile, variance, and effect it used so no input silently mis-sizes the trial.

What it does

Two-sample means: superiority, non-inferiority by a margin, and equivalence (TOST)
Two-sample proportions: superiority (pooled or unpooled) and non-inferiority
Power as the inverse problem for a given per-arm n under the same model
Allocation-ratio scaling (k = n2/n1) with integer ceiling of the required n
High-accuracy inverse-normal quantile (Acklam plus Halley steps, ~1e-9)
Echoes every z-quantile, variance, effect, and margin actually used

Honest scope

Exact here are the normal-approximation closed forms, the inverse-normal quantile, the allocation scaling, and the integer ceiling; sigma, p1, p2 are planning assumptions and the non-inferiority margin is a protocol choice you confirm. Exact tests, t-distribution corrections, continuity correction, survival, repeated-measures, dropout inflation, multiplicity, and adaptive designs are flagged, not computed. Not medical or regulatory advice.

Authorities cited

Size the trial

Set your effect, variance, and design and get the per-arm n or power in the browser - nothing is uploaded. Send results to a Sandbox workspace, a Worklog case, or a Gate client portal.

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