{{ summary.title }}
{{ summary.primary }}
{{ summary.line }}
{{ badge.label }}
Keep it short enough for a filename, protocol code, or randomization appendix.
Example: Intervention | 1 | INT, then Control | 1 | CTL. Ratios must be positive whole numbers.
{{ normalizedParticipantCount }} per stratum
The schedule may be slightly longer when complete blocks are required.
participants
Use comma-separated sizes such as 4, 6, or 8 for a 1:1 trial.
Leave blank for one unstratified list. Keep expected enrollment high enough inside every stratum.
Seeded generation gives an auditable, reproducible browser-local schedule.
{{ seedAuditLine }}
Choose what appears in the schedule table and CSV artifact.
Use opaque codes for envelope labels or import rows; turn off when your EDC supplies IDs.
Random is the normal default; rotate is useful for repeatable QA comparisons.
Complete blocks is safer for allocation balance; trim only when an exact row count is required.
Short prefixes keep the schedule table readable.
Example: RX produces codes such as RX-QM-001.
Seq Participant ID Stratum Block Block size In block Allocation Code Copy
{{ row.sequence }} {{ row.participantId }} {{ row.stratumLabel }} {{ row.blockNumber }} {{ row.blockSize }} {{ row.positionInBlock }} {{ row.allocationDisplay }} {{ row.randomizationCode }}
Stratum Block Size Selection Allocation mix Seed branch Copy
{{ row.stratumLabel }} {{ row.blockNumber }} {{ row.blockSize }} {{ row.selection }} {{ row.mix }} {{ row.seedBranch }}
Scope Arm Observed Expected Delta Signal Copy
{{ row.scope }} {{ row.arm }} {{ row.observed }} {{ row.expected }} {{ row.delta }} {{ row.status }}{{ row.note }} 
{{ scheduleCsv }}
Tags: Productivity, Randomness
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Random assignment is meant to stop enrollment order, investigator preference, and participant characteristics from quietly shaping who receives each treatment. Simple randomization can be enough in large studies, but small trials can drift badly by chance while enrollment is still underway. Block randomization limits that drift by arranging assignments in small groups where each completed block contains the planned arm mix.

A two-arm 1:1 study with block size 4 places two assignments for each arm inside the block, then randomizes their order. A 2:1 study with block size 6 places four assignments for the larger arm and two for the smaller arm. The block protects local balance, while the shuffled order inside each block keeps the next assignment from being a simple alternation.

Permuted block allocation sequence Two strata each receive separate blocks that preserve a one-to-one ratio while shuffling the assignment order. Permuted blocks keep local assignment counts close Each stratum gets its own sequence. Full blocks match the planned arm ratio, then row order is shuffled. Site North INT CTL CTL INT Block ledger: 2 INT, 2 CTL Site South CTL INT INT CTL Same ratio, separate random order

Stratification adds separate lists for meaningful subgroups, such as site, age group, clinic, risk band, or region. This can prevent one subgroup from receiving too many assignments to the same arm early in the study. It also adds management burden. Two factors with two categories each create four schedules, and every extra factor multiplies the number of lists that must be generated, protected, and later reconciled.

The main tradeoff is predictability. Small fixed blocks improve balance, but a visible sequence can make late assignments inside a block easier to guess. Variable block sizes, masked allocation codes, central release procedures, sealed envelopes, or a separate randomization system can reduce that risk. A generated schedule is only the sequence; allocation concealment is the operational process that keeps future assignments unavailable until enrollment is ready.

Choice What it controls Common caution
Arm ratio The intended share of assignments for each group. Every valid block size must fit the ratio cleanly.
Block size How quickly assignment counts return to the planned ratio. Very small known blocks can increase predictability.
Strata Balance inside prespecified subgroups. Too many strata can leave short lists and partial final blocks.
Seed Recreation of the same schedule for review. A seed is not a concealment or security control if it is widely shared.

Block randomization is therefore a design and documentation aid, not a complete trial-control system. The schedule still has to match the protocol, enrollment workflow, data capture process, and analysis plan before it is used for real participants.

How to Use This Tool:

Use the generator to create a reproducible draft schedule, then review warnings, block ledgers, and balance checks before moving any schedule into a controlled study workflow.

  1. Enter a Trial label that will make exported schedules recognizable during review.
  2. Define Treatment arms with one line per arm, using Label | ratio | code. A one-line comma list such as Intervention, Intervention, Control can also express an unequal ratio.
  3. Set Participants per stratum. With stratification, this number applies to each crossed stratum, not to the whole schedule.
  4. Enter Block sizes such as 4, 6. Each valid size must be a positive multiple of the total allocation ratio. Ignored sizes appear in the warning area.
  5. Add Stratification factors as Name: category 1, category 2. Leave the field blank for one unstratified schedule.
  6. Set Seed, Allocation display, and Advanced choices for randomization code column, block selection, final block policy, participant ID prefix, and code prefix.
  7. Review Randomization Schedule, Block Ledger, Balance Checks, and Allocation Balance Chart. Resolve warnings about invalid block sizes, stratum limits, capped assignment counts, overrun rows, or code-display limitations before exporting.
  8. Use Schedule CSV or JSON only after the schedule, block ledger, and balance rows agree with the protocol assumptions.

Interpreting Results:

Start with the schedule rows, then confirm how those rows were produced. The Block Ledger records the block size, whether the block was selected by seeded random choice or rotation, the allocation mix used in that block, and the seed branch shown for audit review. The Balance Checks table compares observed assignments with the expected count overall and within each stratum.

  • Balanced means the observed count is within 0.5 assignment of the ratio target for that scope. It does not prove enrollment, concealment, or analysis quality.
  • Review usually points to a trimmed final block, a small stratum, or a generated scope that cannot land exactly on the ratio.
  • Complete final blocks protect full-block structure but may create extra rows beyond the planned participant count.
  • Trim exactly at participant count keeps the row count exact but can break the planned mix in the last block.
  • Masked arm codes change what appears in schedule output; they do not create blinding or allocation concealment by themselves.

Technical Details:

A permuted block schedule starts with normalized treatment arms and an allocation ratio. Duplicate arm labels are combined, ratios are read as positive whole numbers, and arm codes are cleaned or derived so the schedule can display stable labels. If fewer than two arms are usable, the generator falls back to a sample two-arm setup rather than emitting a one-arm randomization list.

Block size validation is tied to the ratio total. A 1:1 design has ratio total 2, so block sizes such as 4 and 6 are valid. A 2:1 design has ratio total 3, so block sizes such as 3, 6, and 9 are valid. A block size that is smaller than the ratio total or not divisible by the ratio total is ignored and reported.

Rule Core:

Mechanism Rule Effect
Arm parsing Arm lines may use Label | ratio | code, plain labels, or comma lists. Duplicate labels are combined. The schedule uses one normalized entry per arm with a positive whole-number ratio.
Block validation Each block size must be at least the ratio total and divisible by the ratio total. Full blocks can contain exact arm counts for the planned ratio.
Block contents Each arm appears arm ratio x block size / ratio total times inside a full block. A full 1:1 block of 4 has two assignments to each arm; a full 2:1 block of 6 has four and two.
Block order Block size can be selected by seeded random choice or by rotating through the valid sizes. Random selection is closer to production use; rotation makes repeat QA comparisons easier.
Final block Complete blocks keeps the whole last block; Trim cuts the last block at the requested row count. Complete blocks may overrun the plan, while trim may shift final balance.
Strata Factor categories are crossed into separate schedule branches, with a browser-side cap of 64 strata. Each stratum gets its own sequence, but very large factor designs are limited for performance.

Formula Core:

The balance check compares observed arm counts with the count implied by the ratio for the generated scope.

expected arm count = generated rows×arm ratioratio total delta = observed count-expected arm count

For 24 generated rows in a 2:1 design, the larger arm has expected count 24 x 2 / 3 = 16 and the smaller arm has expected count 24 x 1 / 3 = 8. A delta of 0 means the generated rows match the target exactly. A delta whose absolute value is greater than 0.5 is marked for review.

Schedule Flow:

Step What happens Review cue
Normalize inputs Arms, ratios, block sizes, strata, participant count, and code choices are cleaned into a schedule-ready form. Warnings identify fallback arms, ignored blocks, malformed strata, or assignment caps.
Cross strata Each factor category combination becomes an independent schedule branch. Check that each stratum label matches the intended protocol categories.
Build blocks Each branch repeatedly selects a valid block size, expands the arm ratio into block assignments, and shuffles the order. The block ledger should show valid sizes and expected allocation mixes.
Assign rows Participant IDs and optional randomization codes are attached as rows are emitted. Confirm prefixes, code mode, and display mode before sharing schedule files.
Check balance Observed counts are compared with expected ratio counts overall and per stratum. Review nonzero deltas before locking a production schedule.

Seeded reproducibility applies to the same settings. Changing arms, ratios, strata, block sizes, block strategy, final-block policy, participant prefixes, or code mode changes the generated schedule even when the seed text stays the same.

Limitations:

This generator produces a browser-side planning schedule for review. It does not replace a trial statistician, protocol approval, allocation-concealment system, regulatory review, or a controlled release workflow for real participant enrollment.

  • Do not expose upcoming assignments to recruiters, investigators, or site staff who should not know the next allocation.
  • Confirm arm labels, ratios, strata, final-block policy, participant identifiers, and code mode before locking a schedule.
  • Document who generated, reviewed, approved, and released the final schedule.
  • Use masked codes as display labels only; keep a controlled decoding process outside the public enrollment workflow.

Worked Examples:

Two-site 1:1 pilot. A study uses Intervention | 1 | INT and Control | 1 | CTL, sets 24 participants per stratum, enters block sizes 4, 6, and defines Site: North, South. The output should create separate North and South schedules, and each site should be close to 12 INT and 12 CTL assignments.

Unequal 2:1 feasibility study. A design enters New care | 2 | NEW and Usual care | 1 | USU with block sizes 3, 6. If trimming cuts the final block, the balance table may show a small delta. That is a design tradeoff to review rather than a calculation error.

Invalid block correction. A warning says block size 4 was ignored because the ratio total is 3. Replace it with 3, 6, 9, or another positive multiple of 3, then recheck the Block Ledger and Balance Checks.

FAQ:

Can masked codes create blinding?

No. Masked arm codes only change what appears in the generated schedule. Blinding and allocation concealment require controlled procedures outside the generated list.

Why did the schedule create more rows than requested?

Complete blocks finishes the final block even when that goes beyond the planned participant count. Use Trim exactly at participant count when exact row count is more important than final-block completeness.

Why were some block sizes ignored?

Every block size must be a positive multiple of the total arm ratio. For a 2:1 ratio, valid block sizes include 3, 6, 9, and 12.

Does the same seed always produce the same schedule?

Yes, when every schedule setting is the same. Changing arms, strata, block sizes, final-block policy, code settings, or participant count changes the output.

How many strata can I generate?

The generator crosses factor categories into separate strata and caps the browser-side schedule at 64 strata. Reduce factors or categories if a warning says the crossed design was capped.

Glossary:

Arm
A treatment, control, or comparison group that participants can be assigned to.
Allocation ratio
The intended assignment share across arms, such as 1:1 or 2:1.
Block size
The number of assignments grouped together before the next permuted block begins.
Stratum
A subgroup with its own schedule, usually defined by trial factors such as site, age group, or risk category.
Allocation concealment
The operational practice of hiding upcoming assignments from people who enroll participants.
Seed
A repeatable text value used to regenerate the same schedule from the same settings.

References: