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Verifiable Binary Randomisation for Research & Experiments | SpinTheWheel

Establishing a truly random, unbiased assignment mechanism is fundamental when planning an experiment. While complex statistical software often requires technical setups, a simple binary wheel (a 50/50 provably fair spin) offers a clean, transparent, and cryptographically auditable allocation method.

Whether you are assigning matched clinical clusters, setting presentation orders, or randomising an entire dataset of 500+ participants, SpinTheWheel.io provides a free, browser-based solution backed by verifiable cryptographic proofs.

The Power of the Binary (50/50) Model

In research methodology, a binary draw is equivalent to a cryptographically secure coin flip. Each outcome has a strict prior probability of P = 0.50.

By pairing a single binary spin with a pre-defined protocol rule locked prior to execution, researchers can handle complex group assignments while maintaining total compliance with Institutional Review Board (IRB) and peer-review standards.

Common Research Applications

1. Cluster Allocation (1:1 Group Assignment)

When randomising pre-existing cohorts (such as classrooms or regional trial sites), a single binary spin allocates both groups simultaneously, reducing contamination risks.

  • Option A (YES): Cluster 1 Treatment | Cluster 2 Control
  • Option B (NO): Cluster 1 Control | Cluster 2 Treatment

Why it works: Every cluster has an exact 50% probability of being assigned to the intervention. Because the mapping is locked in advance, human selection bias is completely eliminated.


2. Large Participant Datasets (N = 500+)

Randomising hundreds of individual participants does not require spinning a wheel hundreds of times. Instead, researchers use a single verified spin to select between two inverse Master Allocation Schedules:

  • Option A (YES): Odd Participant IDs (1, 3, 5...) Treatment | Even Participant IDs (2, 4, 6...) Control
  • Option B (NO): Even Participant IDs (2, 4, 6...) Treatment | Odd Participant IDs (1, 3, 5...) Control

Statistical Advantages:

  • Equal Probability: Every single subject retains a true 50% chance of receiving Treatment vs. Control.
  • Optimal Balance: Ensures exact 1:1 numerical balance (250 Treatment / 250 Control), preserving statistical power.
  • Order-Bias Protection: Prevents chronological enrolment bias from influencing treatment arms.

3. Presentation & Stimulus Ordering

For counterbalancing in psychological or behavioural studies:

  • Option A: Order 1 (Stimulus A ➡️ Stimulus B)
  • Option B: Order 2 (Stimulus B ➡️ Stimulus A)

Methodological Distinction: Single-Choice vs. Multi-Slice Wheel Configurations

When presenting binary randomisation wheels in a research protocol, it is essential to distinguish between a 2-slice wheel and a multi-slice alternating wheel. While both designs maintain an exact cryptographic 50/50 (P = 0.50) probability distribution, they support fundamentally different experimental workflows.

1. Left Wheel: Single Choice / Cluster Selection (Treatment vs. Control)

  • Core Mechanism: A 2-slice wheel divided evenly into two pre-defined conditions.
  • Protocol Function: Designed to be spun once to select the active condition for a single cluster, matched pair, or master assignment schedule (e.g., YES = Schedule 1; NO = Schedule 2).
  • Best Used For: High-stakes protocol decisions where a single Replay ID locks the master allocation rule for an entire dataset before participant enrolment.

2. Right Wheel: Sequential Draws / Re-Spinning (Alternating Yes / No)

  • Core Mechanism: A multi-slice wheel featuring repeated, alternating 50/50 slices around the circumference.
  • Protocol Function: Designed for sequential individual draws, where the wheel is spun repeatedly (once per subject or trial). Because each alternating slice occupies an identical radial angle, every independent spin preserves a true P = 0.50 probability.
  • Best Used For: Live classroom demonstrations, transparent public draws, or serial participant assignments where each individual event requires its own independent cryptographic verification record.

How Verifiable Randomisation Works on SpinTheWheel

Unlike basic online generators that run unrecorded JavaScript Math.random() scripts, SpinTheWheel uses a Commit-Reveal Cryptographic Protocol (stwspin-hmac-sha256-rejection-v1).

Server Seed Commitment + Client Browser Seed ➡️ HMAC-SHA256 Algorithm ➡️ 1 Single Spin ➡️ Replay ID + Downloadable JSON / PDF Proof

  1. Lock Your Options: Enter your binary choices (Option A / Option B or Yes / No).
  2. Enable Provably Fair Spins: The server commits to a secret value before the spin occurs. Your browser contributes its own seed.
  3. Execute & Archive: Once spun, the system generates a public Replay ID, downloadable JSON audit trail, and a human-readable PDF record.

Anyone (including peer reviewers or study auditors) can open the Replay ID link or inspect the JSON file to verify that the locked inputs match the published outcome.

Documenting the Binary Spin in Your Methodology

To ensure full compliance for journal submissions or pre-registrations (e.g., OSF or ClinicalTrials.gov), record your mapping rule prior to spinning:

Pre-Registration Mapping (Locked Prior to Spin):
  • YES: Schedule 1 (Odd IDs Treatment; Even IDs Control)
  • NO: Schedule 2 (Even IDs Treatment; Odd IDs Control)

Suggested Manuscript Text

"Participant allocation (N = 500) was determined using a pre-specified binary master schedule selected via SpinTheWheel.io. Prior to execution, two inverse assignment schedules were locked in the study protocol. A single provably fair binary spin was conducted to select the active schedule. The resulting Replay ID (Insert Replay ID) and portable JSON proof were archived with the trial documentation."


Instant Academic Citations: Citing Your Verifiable Draw in Academic Publications

Retaining proof of your randomisation is essential for open-science compliance and peer review. SpinTheWheel automatically generates ready-to-use citations in standard reference styles directly from your Verified Spin Record.

Once your provably fair spin is complete, click Copy Citation to export your record in any of the following formats:

APA 7th Edition: Ideal for psychology, social sciences, and health research.

MLA 9th Edition: Standard for humanities and interdisciplinary studies.

Chicago & Harvard: Preferred for medical journals, history, and social science publications.

Vancouver: Commonly required for biomedical and clinical manuscripts.

BibTeX & RIS Exports: One-click downloads to import your record directly into EndNote, Mendeley, or Zotero.

Example Citation Format (If writing or formatting your manuscript bibliography manually, use this structure):

SpinTheWheel.io.Verified spin record. Sealed: [YYYY-MM-DD]. Replay ID: `[Insert Replay ID]`. `https://spinthewheel.io/replay/[Replay ID]`

Complete Archival Package for Peer Review For maximum transparency, journals and Institutional Review Boards (IRBs) recommend archiving the complete verification bundle alongside your study files:

  1. The Replay URL: Links directly to the live, browser-verifiable proof hosted on SpinTheWheel.
  2. The Downloaded JSON Record: Provides an immutable, machine-readable cryptographic proof payload.

Perform Your Verifiable Draw Today

Whether you are conducting a single cluster allocation, selecting a binary master schedule for 500+ participants, or setting up a classroom demonstration, SpinTheWheel.io provides free, auditable, and provably fair randomisation.

  • Commit-Reveal Cryptography: Dual-seed HMAC-SHA256 protocol.
  • Instant Academic Citations: Copy pre-formatted APA 7th, MLA 9th, Chicago, Harvard, RIS, and BibTeX citations.
  • Complete Archival Package: Download portable JSON records and human-readable PDF proofs for peer review and IRB compliance.


Start Your Verifiable Research Draw