Analysis of an Intelligence Dataset

• Other Authors: Myszkowski, Nils (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Psychology; Raven matrices; Standard Progressive Matrices test; dimensionality; bi-factor; parallel analysis; target rotation; exploratory graph analysis; E-assessment; general mental ability; nested logit models; item-response theory; ability-based guessing; Standard Progressive Matrices; Item Response Theory; Bayesian statistics; brms; Stan; R; Raven's progressive matrices; intelligence; distractors; item analysis; intelligence tests; classical test theory; IRT; interaction model; test-item regression; Mokken scale analysis; non-parametric item response theory; psychometrics; invariant item ordering; regularized latent class analysis; regularization; fused regularization; fused grouped regularization; distractor analysis; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven's (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type.