The truly remarkable universality of half a standard deviation: confirmation through another look
Bibliographic record
Abstract
In this issue of Expert Review of Pharmacoeconomics and Outcomes Research, Farivar, Liu, and Hays present their findings in 'Another look at the half standard deviation estimate of the minimally important difference in health-related quality of life scores (hereafter referred to as 'Another look') . These researchers have re-examined the May 2003 Medical Care article 'Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation' (hereafter referred to as 'Remarkable') in the hope of supporting their hypothesis that the minimally important difference in health-related quality of life measures is undoubtedly closer to 0.3 standard deviations than 0.5. Nonetheless, despite their extensive wranglings with the exclusion of many articles that we included in our review; the inclusion of articles that we did not include in our review; and the recalculation of effect sizes using the absolute value of the mean differences, in our opinion, the results of the 'Another look' article confirm the same findings in the 'Remarkable' paper.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.054 | 0.261 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.044 | 0.042 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".