Evidence map›Paper›PMID 26091947›Full record

ArticleContemporary clinical trials2015

Mass weighted urn design--A new randomization algorithm for unequal allocations.

Wenle Zhao

Abstract read
In one paragraph

Article in Contemporary clinical trials, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Trial
  5. Article
  6. Review
  7. Forced randomization: the what, why, and how.BMC medical research methodology · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Wenle ZhaoDepartment of Public Health Sciences, Medical University of South Carolina, 135 Cannon Street, Suite 305H, Charleston, SC 29425, USA. Electronic address: zhaow@musc.edu.

Funding

Workshop to Identify Collaborative Project(s) for the NIH StrokeNet and the Japan NEtwork for Clinical Stroke Trials (NECST)U01NS087748 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI Catherine R. Dillon, Jordan J. Elm · 2014 to 2026
$14.1M
Neurological Emergencies Treatment Trials Network Statistical and Data ManagementU01NS059041 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI DURKALSKI, VALERIE L, PALESCH, YUKO Y · 2006 to 2015
$9.1M
Established Status Epilepticus Treatment Trial (ESETT) - SDMCU01NS088023 · NINDS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI ELM, JORDAN J. · 2014 to 2018
$2.0M
NINDS NIH HHS U01NS0059041NINDS NIH HHS U01 NS059041NINDS NIH HHS U01 NS087748NINDS NIH HHS U01NS087748NINDS NIH HHS U01 NS088023NINDS NIH HHS U01NS088023
6 · The paper itself

Abstract

Unequal allocations have been used in clinical trials motivated by ethical, efficiency, or feasibility concerns. Commonly used permuted block randomization faces a tradeoff between effective imbalance control with a small block size and accurate allocation target with a large block size. Few other unequal allocation randomization designs have been proposed in literature with applications in real trials hardly ever been reported, partly due to their complexity in implementation compared to the permuted block randomization. Proposed in this paper is the mass weighted urn design, in which the number of balls in the urn equals to the number of treatments, and remains unchanged during the study. The chance a ball being randomly selected is proportional to the mass of the ball. After each treatment assignment, a part of the mass of the selected ball is re-distributed to all balls based on the target allocation ratio. This design allows any desired optimal unequal allocations be accurately targeted without approximation, and provides a consistent imbalance control throughout the allocation sequence. The statistical properties of this new design is evaluated with the Euclidean distance between the observed treatment distribution and the desired treatment distribution as the treatment imbalance measure; and the Euclidean distance between the conditional allocation probability and the target allocation probability as the allocation predictability measure. Computer simulation results are presented comparing the mass weighted urn design with other randomization designs currently available for unequal allocations.

Indexed as

AlgorithmsModels, StatisticalRandom AllocationComputer SimulationHumansAllocation predictabilityMass weighted urn designTreatment imbalanceUnequal allocation

Identifiers

PMID26091947
PMCPMC4522356

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.