Relative age effects in the Movement Assessment Battery for Children‐2: age banding and scoring errors
Bibliographic record
Abstract
AIM: The Movement Assessment Battery for Children-2 (MABC-2) uses age-grouped scoring, which will result in relative motor functioning being overestimated for some children and underestimated for others. In this paper, we measure these errors and discuss their consequences. METHOD: We pool data from two validation studies to obtain a sample of 278 children assessed with the MABC-2 (mean (SD) age: 5 years, 0 months (9.6 months); 142 female). We used regression to measure the association between standard score and relative age, and used these results to estimate misclassification rates at the MABC-2's recommended thresholds. RESULTS: Movement Assessment Battery for Children-2 scores were distributed as expected (mean (SD) = 10.4 (2.8)). We estimated that the standard score varied by 2.76 units (0.92 SDs) per year of relative age. Depending on threshold and age bandwidth, this implies overall misclassification rates from 9% to 23%. INTERPRETATION: Relative age differences in MABC-2 scores led to substantial systematic error for young children. These errors can affect MABC-2 validity, longitudinal stability and agreement with other tools, which may reduce the appropriateness of care offered to children. Scoring approaches that may reduce or eliminate these errors are outlined.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".