The Perceptual Maze Test Revisited: Evaluating the Difficulty of Automatically Generated Mazes. (December 2019)

• Record Type: Journal Article
• Authors: Loe, Bao Sheng; Rust, John
• Is Part Of: Assessment. Volume 26:Number 8(2019)
• Page Start: 1524
• Page End: 1539
• Publication Date: 2019-12
• Subjects: perceptual maze test -- exploratory factor analysis -- Rasch model -- LLTM -- automatic item generation; Psychological tests -- Periodicals; Psychodiagnostics -- Periodicals; Personality tests -- Periodicals; 150.287
• DOI: 10.1177/1073191117746501
• Languages: English
• ISSNs: 1073-1911

Abstract

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.