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Analysis of an Intelligence Dataset

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...

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Bibliographic Details
Main Author: Myszkowski, Nils
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Item-response Theory
Fused Regularization
N/a
Ability-based Guessing
Regularized Latent Class Analysis
Stan
Nested Logit Models
Item Analysis
Distractor Analysis
Bayesian Statistics
Brms
Mokken Scale Analysis
Irt
Psychology / Bicssc
Standard Progressive Matrices
E-assessment
Parallel Analysis
Test-item Regression
Target Rotation
Exploratory Graph Analysis
Raven's Progressive Matrices
General Mental Ability
Bi-factor
Standard Progressive Matrices Test
Intelligence Tests
Intelligence
Distractors
Interaction Model
Fused Grouped Regularization
Dimensionality
Raven Matrices
Psychometrics
Invariant Item Ordering
R
Non-parametric Item Response Theory
Regularization
Classical Test Theory
Item Response Theory
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary: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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (166 p.)
ISBN:9783036500409
9783036500416
books978-3-0365-0041-6

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