Bartolucci / Bacci / Gnaldi Statistical Analysis of Questionnaires

A Unified Approach Based on R and Stata
1. Auflage 2015
ISBN: 978-1-4665-6850-1
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 328 Seiten

Reihe: Chapman & Hall/CRC Interdisciplinary Statistics

Statistical Analysis of Questionnaires: A Unified Approach Based on R and Stata presents special statistical methods for analyzing data collected by questionnaires. The book takes an applied approach to testing and measurement tasks, mirroring the growing use of statistical methods and software in education, psychology, sociology, and other fields. It is suitable for graduate students in applied statistics and psychometrics and practitioners in education, health, and marketing.

The book covers the foundations of classical test theory (CTT), test reliability, validity, and scaling as well as item response theory (IRT) fundamentals and IRT for dichotomous and polytomous items. The authors explore the latest IRT extensions, such as IRT models with covariates, multidimensional IRT models, IRT models for hierarchical and longitudinal data, and latent class IRT models. They also describe estimation methods and diagnostics, including graphical diagnostic tools, parametric and nonparametric tests, and differential item functioning.

Stata and R software codes are included for each method. To enhance comprehension, the book employs real datasets in the examples and illustrates the software outputs in detail. The datasets are available on the authors’ web page.

Autoren/Hrsg.

Bartolucci, Francesco

Bacci, Silvia

Gnaldi, Michela

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik

Inhaltsverzeichnis

Preliminaries
Introduction
Psychological Attributes as Latent Variables
Challenges in the Measurement of Latent Constructs
What Is a Questionnaire?
Main Steps in Questionnaire Construction
What Is Psychometric Theory?
Notation
Datasets Used for Examples

Classical Test Theory
Introduction
Foundation
Models
Conceptual Approaches of Reliability
Reliability of Parallel and Nonparallel Tests
Procedures for Estimating Reliability
True Score Estimation
Item Analysis
Validity
Test Bias
Generalizability Theory
Examples

Item Response Theory Models for Dichotomous Items
Introduction
Model Assumptions
Rasch Model
2PL Model
3PL Model
Random-Effects Approach
Summary about Model Estimation
Examples

Item Response Theory Models for Polytomous Items
Introduction
Model Assumptions
Taxonomy of Models for Polytomous Responses
Models for Ordinal Responses
Models for Nominal Responses
Examples

Estimation Methods and Diagnostics
Introduction
Joint Maximum Likelihood Method
Conditional Maximum Likelihood Method
Marginal Maximum Likelihood Method
Estimation of Models for Polytomous Items
Graphical Diagnostic Tools
Goodness-of-Fit
Infit and Outfit Statistics
Differential Item Functioning
Examples
Appendix

Some Extensions of Traditional Item Response Theory Models
Introduction
Models with Covariates
Models for Clustered and Longitudinal Data
Multidimensional Models
Structural Equation Modeling Setting
Examples

Exercises appear at the end of each chapter.

Über Autor(innen)

Francesco Bartolucci is a professor of statistics in the Department of Economics at the University of Perugia. Dr. Bartolucci is an associate editor of Metron and Statistical Modelling: An International Journal. His research interests include latent variable models, marginal models for categorical data, and longitudinal categorical data. He has collaborated with many researchers and published articles on these topics in top statistical journals.

Silvia Bacci is an assistant professor of statistics in the Department of Economics at the University of Perugia. Her research interests include multidimensional and latent class item response theory models and extensions, estimation of item response theory models with R, latent Markov models for multivariate longitudinal data, and the application of these methods and models in educational and quality-of-life settings. She has published articles on these topics in international journals and participated in several research projects.

Michela Gnaldi is an assistant professor of applied statistics in the Department of Political Sciences at the University of Perugia. She is editorial manager of the Italian Journal of Applied Statistics. Her main research interest concerns measurement in education, with particular regard to multidimensional, multilevel, and latent class item response theory models. She has published articles on these topics in international journals and participated in several projects in Italy and the United Kingdom. She actively collaborates with the "Istituto Nazionale di Valutazione del Sistema dell’Istruzione" (INVALSI).