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Generate Reproducible Blocked Treatment Assignments from a Visible Seed

Allocate participant IDs across arms inside blocks while preserving exact counts and audit order.

Drop or choose a file up to 2 MB. Its contents replace the main text input; the filename alone is never treated as data.

Reviewable output

Processed

Warnings / conflicts

Output state

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How the calculation works

Local inputboundedPer-item ruledeterministicArtifactcopy / download

How to Use This Tool

Allocate participant IDs across arms inside blocks while preserving exact counts and audit order. Generate deterministic blocked experiment assignments from IDs, block labels, treatment ratios and a visible seed, then export an auditable CSV plan.

The work this page finishes

Assignments made ad hoc can drift from the declared ratio or become impossible to reproduce, especially when separate sites or cohorts must remain balanced. For Randomization Plan, the row-preserving workspace makes a correction repeatable without rebuilding a prompt or transmitting the source file.

Rows or choicesValidate every itemReview and export
The sample assigns six IDs within two site blocks to control and treatment using a reproducible 1:1 cycle and seed 42.

Deterministic workflow

Validate unique participant IDs and weighted arms, group by the supplied block, sort each block with a visible seeded hash and cycle through the declared allocation ratio. For Randomization Plan, this page accepts at most 5,000 records and 2 MB of text; rejected items retain their row references while valid items remain available.

Why a dedicated interface helps

Freeze the exported plan before enrollment or analysis and have the study owner review concealment, ethics, power and the approved randomization procedure. For Randomization Plan, immediate recalculation and a stable export are useful when the same rule must be applied consistently across a list instead of explained one item at a time.

Assumptions

  • Participant IDs are non-sensitive test or approved identifiers.
  • Blocks are declared before assignment.
  • Weights describe the intended within-block cycle.

For Randomization Plan, retain the original source until the destination accepts the result; processing stays in this tab, although the device and installed extensions remain part of the user's security boundary.

Limitations and review boundary

This is planning software, not a clinical randomization service; it is not cryptographically unpredictable and does not provide allocation concealment, power analysis or regulatory compliance. For Randomization Plan, no supplied URL is requested and no pasted markup or code is executed; output is inserted through text-only DOM operations.

Verification and provenance

The implementation was checked against NIST/SEMATECH e-Handbook — Randomization on 2026-08-26, with fixtures for a known answer, an invalid input and a batch-specific edge condition. The sample assigns six IDs within two site blocks to control and treatment using a reproducible 1:1 cycle and seed 42.

Sources & assumptions

Tool Spec v2 · verified 2026-08-26. Platform rules and fees can change; the editable inputs remain authoritative for your account.

Official references

Model assumptions

  • Participant IDs are non-sensitive test or approved identifiers.
  • Blocks are declared before assignment.
  • Weights describe the intended within-block cycle.
  • This is planning software, not a clinical randomization service; it is not cryptographically unpredictable and does not provide allocation concealment, power analysis or regulatory compliance.
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Frequently Asked Questions

What does Randomization Plan complete?
It applies the stated generator rule to randomization plan inputs and produces the reviewable output shown above.
Why use a dedicated Randomization Plan page instead of chat?
The Randomization Plan workflow preserves ordering, applies identical validation on every run and creates an artifact without conversational drift.
Does Randomization Plan send the input to ecech?
No. Randomization Plan reads pasted or selected content inside the current browser tab and does not call an ecech calculation API.
What verifies the default result?
The sample assigns six IDs within two site blocks to control and treatment using a reproducible 1:1 cycle and seed 42.
When should I reject the output?
This is planning software, not a clinical randomization service; it is not cryptographically unpredictable and does not provide allocation concealment, power analysis or regulatory compliance.
Which reference supports Randomization Plan?
The recorded Randomization Plan reference is NIST/SEMATECH e-Handbook — Randomization, reviewed 2026-08-26.

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