Introducing equating methodologies to compare test scores from two different self-regulation scales
Bibliographic record
Abstract
Standardizing the measurement tools that researchers use to assess the effectiveness of interventions would strengthen our ability to compare results across studies. In practice, however, standardization is difficult to implement, in part, because researchers prefer to use measurement tools that focus specifically on the components of their interventions. This paper demonstrates the usefulness of item response modeling linking methodology in comparing groups of participants who were administered different scales intended to measure the same underlying constructs. The Treatment Self-Regulation Questionnaire (TSRQ) as it relates to diet improvement provided the empirical application to demonstrate how two different scales that measure the same construct can be compared. The results showed that two eight-item TSRQ scales can be linked if they have at least four items in common. As expected, varying the number of linking items did not affect the reliability of the results; however, it significantly affected the relative rating with respect to the 15-item scale. In health behavior and health education research, linking methodologies can be used to compare results across studies that use slightly different versions of a scale to measure the same construct.
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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 | 0.298 | 0.608 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".