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Properties of the estimated variance component for subject-by-formulation interaction in studies of individual bioequivalence

2000· article· en· W2069688121 on OpenAlex

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A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueStatistics in Medicine · 2000
Typearticle
Languageen
FieldMathematics
TopicStatistical Methods in Clinical Trials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBioequivalenceVariance (accounting)StatisticsRestricted maximum likelihoodEconometricsVariance componentsComponent (thermodynamics)MathematicsMaximum likelihoodMedicineEconomicsPharmacology

Abstract

fetched live from OpenAlex

Characteristics of the variance component for the subject-by-formulation interaction (sigma(2)(D)), estimated in simulated studies of individual bioequivalence and in three- and four-period cross-over trials reported by the FDA, were compared. sigma(2)(D) was estimated by (i) restricted maximum likelihood (REML) and (ii) the method of moments (MM). Variation of the variance component, estimated by both procedures (s(2)(D)) and for both the simulated and FDA data, increased with rising intra-individual variation. Consequently, a constant level of s(2)(D) (such as 0.0225 suggested by the FDA) may not be regarded as a basis for demonstrating substantial interactions. Features of the FDA and simulated parameters were similar. The results suggested that the FDA data were compatible with assuming sigma(D)=0.05 or perhaps 0.00. Therefore, there is no foundation for concerns about public health. Both simulations and calculations demonstrated that s(2)(D) estimated by MM was unbiased and its variance was proportional to sigma(4)(WF) when sigma(2)(D)=0.

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.

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)0.003
metaresearch head score (Gemma)0.066
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.606
GPT teacher head0.572
Teacher spread0.034 · 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