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Record W2006934976 · doi:10.1177/0272989x0202200413

How Robust Is the Health Utilities Index Mark 2 Utility Function?

2002· article· en· W2006934976 on OpenAlexaff
Qinan Wang, William Furlong, David Feeny, George W. Torrance, Ronald D. Barr

Bibliographic record

VenueMedical Decision Making · 2002
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsMcMaster UniversityMcMaster Children's HospitalHamilton Health SciencesInstitute of Health Economics
Fundersnot available
KeywordsIndex (typography)Function (biology)Health Utilities IndexQuality-adjusted life yearEconometricsActuarial scienceEconomicsComputer scienceMedicineOperations managementHealth related quality of lifeDiseaseCost effectiveness

Abstract

fetched live from OpenAlex

PURPOSE: The utility function for the Health Utilities Index Mark 2 (HUI2) system is based on preference measurements from a random sample of parents with exclusion of inconsistent respondents. Would results without exclusions or from a different group of parents have differed? METHODS: Scores were obtained from parents of patients (n = 59) undergoing treatment for cancer. Mean scores from the 2 sets of parents were compared:parents of patients and parents from the general population. Three multiattribute utility functions were estimated. Mean scores for HUI2 states using the functions were compared. RESULTS: Most differences in mean scores between different groups were not statistically significant (P < 0.05). Differences in parameter estimates among the 3 utility functions were 0.05 or less. The exponent on the power function for the parent-of-patient group was 2.16, within 6% of that for random sample parents. The intraclass correlation between scores for 144 health states derived from the random-sample-parents and parents-of-patients functions was 0.99; the mean difference per state in scores was 0.018. CONCLUSION: The HUI2 scoring function generalizes well in that different groups of parents give similar results. The HUI2 scoring function is robust in that the functions without and with exclusions generate scores that are very close in value.

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)0.025
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0170.002

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 head0.415
GPT teacher head0.425
Teacher spread0.010 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations14
Published2002
Admission routes1
Has abstractyes

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