The Perceptual Maze Test Revisited: Evaluating the Difficulty of Automatically Generated Mazes.
LLTM
Rasch model
automatic item generation
exploratory factor analysis
perceptual maze test
Journal
Assessment
ISSN: 1552-3489
Titre abrégé: Assessment
Pays: United States
ID NLM: 9431219
Informations de publication
Date de publication:
12 2019
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