Measurement models for psychological attributes / Klaas Sijtsma, L.Andries van der Ark.

Format:

Book

Author/Creator:

Sijtsma, K. (Klaas), 1955- author.

Ark, L. Andries van der, author.

Series:

Statistics in the social and behavioral sciences series

Chapman & Hall/CRC statistics in the social and behavioral sciences

Language:

English

Subjects (All):

Psychology--Research--Methodology.

Psychology.

Psychology--Mathematical models.

Physical Description:

xx, 407 pages : illustrations ; 24 cm.

Place of Publication:

Boca Raton ; London ; New York : CRC Press, Taylor & Francis Group, [2021]

Summary:

"Despite the overwhelming use of tests and questionnaires, the psychometric models for constructing these instruments are often poorly understood, leading to suboptimal measurement. Measurement Models for Psychological Attributes is a comprehensive and accessible treatment of the common and the less than common measurement models for the social, behavioral, and health sciences. The monograph explains the adequate use of measurement models for test construction, points out their merits and drawbacks, and critically discusses topics that have raised and continue to raise controversy. Because introductory texts on statistics and psychometrics are sufficient to understand its content, the monograph may be used in advanced courses on applied psychometrics and is attractive to both researchers and graduate students in psychology, education, sociology, political science, medicine and marketing, policy research, and opinion research." --From publisher's description.

Contents:

Machine generated contents note: 1. Measurement in the Social, Behavioral, and Health Sciences

Introduction

Methodological Procedures and Psychometric Measurement Models

Relation of Measurement Model to Attribute Scale

Developing Attribute Theory Is Important

Measurement Instruments

Measurement Models

Scales of Measurement

Causes of Messy Data

A Scale for Transitive Reasoning

Cycle of Instrument Construction

This Monograph

2. Classical Test Theory and Factor Analysis

Historical Introduction

The Classical Test Model

Measurement Level and Norm Scores

Model Assumptions

Repeatability of Test Scores: Reliability

Methods for Estimating Reliability

Methods Commonly Used in Test-Construction Practice

Parallel-Test Method

Retest Method

Split-Half Method

Internal Consistency Method

Reliability Methods Based on One Test Administration

Method (Sn (B1

Method (Sn (B3

Method (Sn (B2

Method (Sn (B4

Method (Sn (B5

Method (Sn (B6

Greatest Lower Bound

Special Topics Concerning Methods (Sn (B1 through (Sn (B6 and the GLB

Mutual Relationships of Lower Bounds and Reliability

Discrepancy of Methods (Sn (B1 through (Sn (B6 and the GLB

Overestimation of Reliability in Real Data

Confidence Intervals

Reliability versus Measurement Precision

Traditional Methods

Alternative Methods and Special Topics

Constructing Scales in the Classical Test Theory Context

Corrected Item-Total Correlations and Oblique Multiple Group Method

Principal Component Analysis

Factor Analysis

Factor-Analysis Approach to Reliability

One-Factor Model

Multi-Factor Model

Real-Data Example: The Type D Scalel4 (DS14)

Discussion

3. Nonparametric Item Response Theory and Mokken Scale Analysis

Model of Monotone Homogeneity

Prerequisites

Definitions and Notation

Assumptions

Strictly and Essentially Unidimensional IRT

An Ordinal Scale for Person Measurement

Goodness-of-Fit Methods

Unidimensionality: Scalability and Item Selection

Local Independence

Monotonicity

Data Example: The Type D Scalel4 (DS14) Revisited Using Nonparametric IRT

Model of Double Monotonicity

Method Manifest Invariant Item Ordering

Other Methods for Investigating Manifest Invariant Item Ordering

Reliability

Data Example: The Type D Scale14 (DS14) Continued

4. Parametric Item Response Theory and Structural Extensions

A Taxonomy for IRT Models

Some Basic IRT Models for Dichotomous Items

Guttman Model

Normal-Ogive Models

One-Parameter Logistic Model or Rasch Model

The Model, Separability of Parameters

Sufficiency and Estimation

Information Functions and Measurement Precision

The Rasch Paradox

Epilogue

Two and Three-Parameter Logistic Models

Some Basic IRT Models for Polytomous Items

Adjacent Category Models

Cumulative Probability Models

Continuation Ratio Models

Filling in the Taxonomy

IRT Models for Special Purposes

Linear Logistic Test Model

Generalized Rasch Model with Manifest Predictors

Multidimensional IRT Models

Data Example: Transitive Reasoning

5. Latent Class Models and Cognitive Diagnostic Models

Latent Class Model

An Example: Proportional Reasoning

The Unrestricted Model

Restricted Models

Estimation

Ordered LCM and Testing Monotonicity in Nonparametric IRT

Data Example: Proportional Reasoning by Means of the Balance Scale

Cognitive Diagnostic Model

An Example: Identifying Patients' Disorder Profiles Using the MCMI-III

Models

Relationship to Nonparametric IRT

Data Example: Identifying Patients' Disorder Profiles Using the MCMI-III

General Discussion

6. Pairwise Comparison, Proximity, Response Time, and Network Models

Pairwise Comparison Models

Thurstone Model

Bradley

Terry

Luce Model

Proximity Models

Deterministic Model

Probabilistic Models

Response Time Models

Lognormal Model

Diffusion Model

Network Psychometrics

Network Approach for Gaussian Data

Prerequisites for Gaussian Data Networks

Networks for Gaussian Data

Network Approach for Binary Data

Discussion.

Notes:

Includes bibliographical references and index.

Other Format:

ebook version :

ISBN:

0367424525

9780367424527

9781439881347

1439881340

OCLC:

1110440661

Publisher Number:

99989358705