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Record W1966169084 · doi:10.1177/0013164410387382

Invariance of the Measurement Model Underlying the Wechsler Adult Intelligence Scale-IV in the United States and Canada

2010· article· en· W1966169084 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueEducational and Psychological Measurement · 2010
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsUniversity of CalgaryBC Mental Health & Substance Use ServicesUniversity of British Columbia
FundersAmerican Psychological AssociationAmerican Educational Research Association
KeywordsPsychologyWechsler Adult Intelligence ScaleMeasurement invarianceNormativeGeneralityConstruct validityIntelligence quotientLatent variableWechsler Preschool and Primary Scale of IntelligencePsychometricsCognitionDevelopmental psychologyConstruct (python library)Scale (ratio)Set (abstract data type)Latent variable modelWechsler Intelligence Scale for ChildrenSample (material)StatisticsConfirmatory factor analysisStructural equation modelingMathematics

Abstract

fetched live from OpenAlex

A measurement model describes both the numerical and theoretical relationship between observed scores and the corresponding latent variables or constructs. Testing a measurement model across groups is required to determine if the tests scores are tapping the same constructs so that the same meaning can be ascribed to the scores. Contemporary tests of intelligence describe a number of closely related cognitive abilities, each ability being sampled by a set of observed scores. This study examined the invariance of the measurement model underlying the Wechsler Adult Intelligence Scale—IV (WAIS-IV) in the U.S. and the Canadian standardization samples. The model satisfied the assumption of invariance across samples with subtest scores reflecting similar construct measurement in both samples. Consistent with previous research with the WAIS-III, slightly higher latent variable means were found in the Canadian WAIS-IV normative sample. The results demonstrate the generality of construct validity in measurement of cognitive abilities across U.S. and Canadian samples and highlight the importance of local norms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.859

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.239
GPT teacher head0.355
Teacher spread0.116 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it