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Record W2150911897 · doi:10.1155/s0161171201005750

Play‐the‐winner rule and adaptive designs of clinical trials

2001· article· en· W2150911897 on OpenAlexafffund
Xikui Wang, Daryl Pullman

Bibliographic record

VenueInternational Journal of Mathematics and Mathematical Sciences · 2001
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsMemorial University of NewfoundlandUniversity of Manitoba
FundersFaculty of Medicine, Memorial University of NewfoundlandMemorial University of Newfoundland
KeywordsInterchangeabilityRegretSimple (philosophy)MathematicsAdaptive designMathematical optimizationClinical trialArtificial intelligenceComputer scienceStatisticsMedicine

Abstract

fetched live from OpenAlex

In another paper, we have argued that the traditional randomized design of clinical trials is ethically infeasible in desperate medical situations and adaptive designs are morally required. We have also argued that in such situations, the appropriate designs must satisfy what we call the “Principle of interchangeability.” In this statistics paper, we show that the statistical model of bandit processes satisfies this principle of interchangeability. Moreover, we demonstrate that when such a model is used as an adaptive design, the total regret of successes lost is smaller when compared with simple randomization. We illustrate the results by the simple deterministic play‐the‐winner design.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.047
metaresearch head score (Gemma)0.178
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.195
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0470.178
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.846
GPT teacher head0.661
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2001
Admission routes2
Has abstractyes

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