A Systematic Literature Review on the Application of Rasch Analysis in Musculoskeletal Disease — A Special Interest Group Report of OMERACT 11
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The Rasch measurement model provides robust analysis of the internal construct validity of outcome measures. We reviewed the application of Rasch analysis in musculoskeletal medicine as part of the work leading to discussion in a Special Interest Group in Rasch Analysis at Outcome Measures in Rheumatology 11. METHODS: A systematic literature review of SCOPUS and MEDLINE was performed (January 1, 1985, to February 29, 2012. Original research reports in English using "Rasch" or "Item Response Theory" in musculoskeletal diseases were assessed by 2 independent reviewers. The topics of focus and analysis methodology details were recorded. RESULTS: Of 212 articles reviewed, 114 were included. The number of publications rose from 1 in 1991-1992 to 23 in 2011-February 2012. Disease areas included rheumatoid arthritis (28%), osteoarthritis (16.6%), and general musculoskeletal disorders (43%). Sixty-six reports (57.9%) evaluated psychometric properties of existing scales and 35 (30.7%) involved development of new scales. Nine articles (7.9%) were on methodology illustration. Four articles were on item banking and computer adaptive testing. A majority of the articles reported fit statistics, while the basic Rasch model assumption (i.e., unidimensionality) was examined in only 57.2% of the articles. An improvement in reporting qualities with Rasch articles was noted over time. In addition, only 11.4% of the articles provided a transformation table for interval scale measurement in clinical practice. CONCLUSION: The Rasch model has been increasingly used in rheumatology over the last 2 decades in a wide range of applications. The majority of the articles demonstrated reasonable quality of reporting. Improvements in quality of reporting over time were revealed.
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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 | 0.032 | 0.129 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it