Validity of the<i>Motor-Free Visual Perceptual Test—Revised (MVPT-R)</i>: An Item Response Analysis
Bibliographic record
Abstract
Background: Visual perceptual skills of children are often evaluated. The Motor-Free Visual Perception Test-Revised (MVPT-R) is one of the most frequently used tests with school-age children even though its construct validity has not been thoroughly evaluated. Aim/Purpose: The purpose of the study was to evaluate the scalability/interval level measurement, unidimensionality, lack of differential item functioning (DIF), and hierarchical ordering of items of the MVPT-R. Method: The visual perceptual performance scores from a sample of 356 normally developing children (171 boys and 185 girls) ranging in age from 5 to 11 years were used to complete a Rasch Measurement Model (RMM) analysis of the MVPT-R. Results: When the MVPT-R was analyzed using the RMM, it exhibited adequate measurement properties (scalability/interval level measurement, unidimensionality, lack of DIF, and hierarchical ordering). However, many MVPT-R scale items exhibited RMM misfit or DIF. Conclusion: The construct validity, scalability, hierarchical ordering, and lack of DIF requirements were met by the final version of the of the MVPT-R scale. However, given the fact that a number of items exhibited RMM misfit or DIF, clinicians need to take this into consideration when using the MVPT-R in its current form.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".