The Underlining Test: An exploration of its construct dimensions in a clinic-referred sample.
Bibliographic record
Abstract
The present study examined the number and nature of factors underlying performance on The Underlining Test (UT), a set of 14 speeded cancellation tasks (subtests) containing letters, digits or shapes, separately or in strings. Using data from a large (n = 844) heterogeneous sample of clinic-referred children, several hypothesized models containing one to four latent constructs were examined using confirmatory factor analysis. A four-factor model had the best fit to the data, and based on the nature of the subtests associated with each construct they were labeled Individual Item Search, Reading-Related, Sequencing, and Complex Visual Analysis. Composite scores were calculated for each factor and compared to several tests of neuropsychological functioning and measures of academic achievement. Only limited information was found regarding the concurrent validity of these factors. Most correlations with neuropsychological tests were small, but the Reading-Related and Sequencing factors had moderate correlations with measures of academic achievement. Several subsequent post hoc analyses revealed that processing speed might play a significant role in UT performance, particularly for the Individual Item Search factor. These results support the hypothesis that the subtests of the UT measure multiple cognitive constructs to varying degrees. They also provide evidence that its factors are primarily sensitive to reading skills, spelling, and processing speed. The UT has the potential to be a valuable tool for researchers and clinicians to examine patterns of neuropsychological functioning in children.Dept. of Psychology. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2003 .H39. Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5271. Adviser: Byron P. Rourke. Thesis (Ph.D.)--University of Windsor (Canada), 2003.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".