Cost‐effectiveness analysis when the WTA is greater than the WTP
Bibliographic record
Abstract
The incremental cost effectiveness ratio has long been the standard parameter of interest in the assessment of the cost-effectiveness of a new treatment. However, due to concerns with interpretability and statistical inference, authors have suggested using the willingness-to-pay for a unit of health benefit to define the incremental net benefit as an alternative. The incremental net benefit has a more consistent interpretation and is amenable to routine statistical procedures. These procedures rely on the fact that the willingness-to-accept compensation for a loss of a unit of health benefit (at some cost saving) is the same as the willingness-to-pay for it. Theoretical and empirical evidence suggest, however, that in health care the willingness-to-accept is about twice as much as the willingness-to-pay. We use Bayesian methods to provide a statistical procedure for the cost-effectiveness comparison of two arms of a randomized clinical trial that allows the willingness-to-pay and the willingness-to-accept to have different values. An example is provided.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".