The Perceptual Maze Test Revisited: Evaluating the Difficulty of Automatically Generated Mazes.


Journal

Assessment
ISSN: 1552-3489
Titre abrégé: Assessment
Pays: United States
ID NLM: 9431219

Informations de publication

Date de publication:
12 2019
Historique:
pubmed: 15 12 2017
medline: 30 10 2020
entrez: 15 12 2017
Statut: ppublish

Résumé

The Elithorn perceptual maze test is widely used in clinical research and practice. However, there is little evidence of its psychometric properties, and its application is limited by the technical difficulty of developing more mazes. The current research aims to adopt a rigorous approach to evaluate 18 mazes that were automatically generated by a novel R software package. Various item response theory models were employed to examine the difficulty parameters. The findings suggested that the data best fitted the Rasch model. The linear logistic test model revealed meaningful contribution to the sources of maze difficulty. Additionally, the linear logistic test model plus error was considered the most parsimonious model. The Automatic Perceptual Maze Test was moderately correlated with a nonverbal intelligence test. By introducing more mazes to provide adequate information on participants' ability at all levels, the Automatic Perceptual Maze Test promises future clinical and research utility for the study of cognitive performance.

Identifiants

pubmed: 29239208
doi: 10.1177/1073191117746501
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1524-1539

Auteurs

Bao Sheng Loe (BS)

University of Cambridge, Cambridge, UK.

John Rust (J)

University of Cambridge, Cambridge, UK.

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Classifications MeSH