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Author: Tenko Raykov
Publisher:
ISBN: 9781597182683
Category : Social Science
Languages : en
Pages : 270
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Book Description
Over the past several decades, item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral, educational, social, business, marketing, clinical, and health sciences. In this book, Raykov and Marcoulides begin with a nontraditional approach to IRT and IRM that is based on their connections to classical test theory, (nonlinear) factor analysis, generalized linear modeling, and logistic regression. Application-oriented discussions follow next. These cover the one-, two-, and three-parameter logistic models, polytomous item response models (with nominal or ordinal items), item and test information functions, instrument construction and development, hybrid models, differential item functioning, and an introduction to multidimensional IRT and IRM. The pertinent analytic and modeling capabilities of Stata are thoroughly discussed, highlighted, and illustrated on empirical examples from behavioral and social research.
Author: Tenko Raykov
Publisher:
ISBN: 9781597182683
Category : Social Science
Languages : en
Pages : 270
Get Book Here
Book Description
Over the past several decades, item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral, educational, social, business, marketing, clinical, and health sciences. In this book, Raykov and Marcoulides begin with a nontraditional approach to IRT and IRM that is based on their connections to classical test theory, (nonlinear) factor analysis, generalized linear modeling, and logistic regression. Application-oriented discussions follow next. These cover the one-, two-, and three-parameter logistic models, polytomous item response models (with nominal or ordinal items), item and test information functions, instrument construction and development, hybrid models, differential item functioning, and an introduction to multidimensional IRT and IRM. The pertinent analytic and modeling capabilities of Stata are thoroughly discussed, highlighted, and illustrated on empirical examples from behavioral and social research.
Author: Tenko Raykov
Publisher:
ISBN: 9781597182669
Category : Item reponse modeling
Languages : en
Pages : 270
Get Book Here
Book Description
Over the past several decades, item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral, educational, social, business, marketing, clinical, and health sciences. In this book, Raykov and Marcoulides begin with a nontraditional approach to IRT and IRM that is based on their connections to classical test theory, (nonlinear) factor analysis, generalized linear modeling, and logistic regression. Application-oriented discussions follow next. These cover the one-, two-, and three-parameter logistic models, polytomous item response models (with nominal or ordinal items), item and test information functions, instrument construction and development, hybrid models, differential item functioning, and an introduction to multidimensional IRT and IRM. The pertinent analytic and modeling capabilities of Stata are thoroughly discussed, highlighted, and illustrated on empirical examples from behavioral and social research.
Author: Insu Paek
Publisher: Routledge
ISBN: 1351008153
Category : Psychology
Languages : en
Pages : 272
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Book Description
Item response theory (IRT) is widely used in education and psychology and is expanding its applications to other social science areas, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors, practitioners, and applied researchers who want to learn how to properly use R IRT packages to perform IRT model calibrations with their own data. This book provides practical line-by-line descriptions of how to use R IRT packages for various IRT models. The scope and coverage of the modeling in the book covers almost all models used in practice and in popular research, including: dichotomous response modeling polytomous response modeling mixed format data modeling concurrent multiple group modeling fixed item parameter calibration modelling with latent regression to include person-level covariate(s) simple structure, or between-item, multidimensional modeling cross-loading, or within-item, multidimensional modeling high-dimensional modeling bifactor modeling testlet modeling two-tier modeling For beginners, this book provides a straightforward guide to learn how to use R for IRT applications. For more intermediate learners of IRT or users of R, this book will serve as a great time-saving tool for learning how to create the proper syntax, fit the various models, evaluate the models, and interpret the output using popular R IRT packages.
Author: Tenko Raykov
Publisher: Routledge
ISBN: 1136900020
Category : Psychology
Languages : en
Pages : 602
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Book Description
This new text provides a state-of the-art introduction to educational and psychological testing and measurement theory that reflects many intellectual developments of the past two decades. The book introduces psychometric theory using a latent variable modeling (LVM) framework and emphasizes interval estimation throughout, so as to better prepare readers for studying more advanced topics later in their careers. Featuring numerous examples, it presents an applied approach to conducting testing and measurement in the behavioral, social, and educational sciences. Readers will find numerous tips on how to use test theory in today’s actual testing situations. To reflect the growing use of statistical software in psychometrics, the authors introduce the use of Mplus after the first few chapters. IBM SPSS, SAS, and R are also featured in several chapters. Software codes and associated outputs are reviewed throughout to enhance comprehension. Essentially all of the data used in the book are available on the website. In addition instructors will find helpful PowerPoint lecture slides and questions and problems for each chapter. The authors rely on LVM when discussing fundamental concepts such as exploratory and confirmatory factor analysis, test theory, generalizability theory, reliability and validity, interval estimation, nonlinear factor analysis, generalized linear modeling, and item response theory. The varied applications make this book a valuable tool for those in the behavioral, social, educational, and biomedical disciplines, as well as in business, economics, and marketing. A brief introduction to R is also provided. Intended as a text for advanced undergraduate and/or graduate courses in psychometrics, testing and measurement, measurement theory, psychological testing, and/or educational and/or psychological measurement taught in departments of psychology, education, human development, epidemiology, business, and marketing, it will also appeal to researchers in these disciplines. Prerequisites include an introduction to statistics with exposure to regression analysis and ANOVA. Familiarity with SPSS, SAS, STATA, or R is also beneficial. As a whole, the book provides an invaluable introduction to measurement and test theory to those with limited or no familiarity with the mathematical and statistical procedures involved in measurement and testing.
Author: Steven P. Reise
Publisher: Routledge
ISBN: 131756569X
Category : Psychology
Languages : en
Pages : 710
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Book Description
Item response theory (IRT) has moved beyond the confines of educational measurement into assessment domains such as personality, psychopathology, and patient-reported outcomes. Classic and emerging IRT methods and applications that are revolutionizing psychological measurement, particularly for health assessments used to demonstrate treatment effectiveness, are reviewed in this new volume. World renowned contributors present the latest research and methodologies about these models along with their applications and related challenges. Examples using real data, some from NIH-PROMIS, show how to apply these models in actual research situations. Chapters review fundamental issues of IRT, modern estimation methods, testing assumptions, evaluating fit, item banking, scoring in multidimensional models, and advanced IRT methods. New multidimensional models are provided along with suggestions for deciding among the family of IRT models available. Each chapter provides an introduction, describes state-of-the art research methods, demonstrates an application, and provides a summary. The book addresses the most critical IRT conceptual and statistical issues confronting researchers and advanced students in psychology, education, and medicine today. Although the chapters highlight health outcomes data the issues addressed are relevant to any content domain. The book addresses: IRT models applied to non-educational data especially patient reported outcomes Differences between cognitive and non-cognitive constructs and the challenges these bring to modeling. The application of multidimensional IRT models designed to capture typical performance data. Cutting-edge methods for deriving a single latent dimension from multidimensional data A new model designed for the measurement of constructs that are defined on one end of a continuum such as substance abuse Scoring individuals under different multidimensional IRT models and item banking for patient-reported health outcomes How to evaluate measurement invariance, diagnose problems with response categories, and assess growth and change. Part 1 reviews fundamental topics such as assumption testing, parameter estimation, and the assessment of model and person fit. New, emerging, and classic IRT models including modeling multidimensional data and the use of new IRT models in typical performance measurement contexts are examined in Part 2. Part 3 reviews the major applications of IRT models such as scoring, item banking for patient-reported health outcomes, evaluating measurement invariance, linking scales to a common metric, and measuring growth and change. The book concludes with a look at future IRT applications in health outcomes measurement. The book summarizes the latest advances and critiques foundational topics such a multidimensionality, assessment of fit, handling non-normality, as well as applied topics such as differential item functioning and multidimensional linking. Intended for researchers, advanced students, and practitioners in psychology, education, and medicine interested in applying IRT methods, this book also serves as a text in advanced graduate courses on IRT or measurement. Familiarity with factor analysis, latent variables, IRT, and basic measurement theory is assumed.
Author: Anders Skrondal
Publisher: CRC Press
ISBN: 0203489438
Category : Mathematics
Languages : en
Pages : 528
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Book Description
This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wi
Author: Scott A. Baldwin
Publisher:
ISBN: 9781597183031
Category : Psychology
Languages : en
Pages : 454
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Book Description
"Psychological statistics and psychometrics using Stata by Scott Baldwin is a complete and concise resource for students and researchers in the behavioral sciences. Professor Baldwin includes dozens of worked examples using real data to illustrate the theory and concepts. This book would be an excellent textbook for a graduate-level course in psychometrics. It is also an ideal reference for psychometricians who are new to Stata. Baldwin's primary goal in this book is to help readers become competent users of statistics. To that end, he first introduces basic statistical methods such as regression, t tests, and ANOVA. He focuses on explaining the models, how they can be used with different types of variables, and how to interpret the results. After building this foundation, Baldwin covers more advanced statistical techniques, including power-and-sample size calculations, multilevel modeling, and structural equation modeling. This book also discusses measurement concepts that are crucial in psychometrics. For instance, Baldwin explores how reliability and validity can be understood and evaluated using exploratory and confirmatory factor analysis. Baldwin includes dozens of worked examples using real data to illustrate the theory and concepts. In addition to teaching statistical topics, this book helps readers become proficient Stata users. Baldwin teaches Stata basics ranging from navigating the interface to using features for data management, descriptive statistics, and graphics. He emphasizes the need for reproducibility in data analysis; therefore, he is careful to explain how version control and do-files can be used to ensure that results are reproducible. As each statistical concept is introduced, the corresponding commands for fitting and interpreting models are demonstrated. Beyond this, readers learn how to run simulations in Stata to help them better understand the models they are fitting and other statistical concepts. This book is an excellent textbook for graduate-level courses in psychometrics. It is also an ideal reference for psychometricians and other social scientists who are new to Stata"--Publisher's website.
Author: James W. Hardin
Publisher: Stata Press
ISBN: 1597180149
Category : Computers
Languages : en
Pages : 413
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Book Description
Deftly balancing theory and application, this book stands out in its coverage of the derivation of the GLM families and their foremost links. This edition has new sections on discrete response models, including zero-truncated, zero-inflated, censored, and hurdle count models, as well as heterogeneous negative binomial, and more.
Author: Kevin J. Grimm
Publisher: Guilford Publications
ISBN: 1462526063
Category : Social Science
Languages : en
Pages : 558
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Book Description
Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.
Author: Kenneth Train
Publisher: Cambridge University Press
ISBN: 0521766559
Category : Business & Economics
Languages : en
Pages : 399
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Book Description
This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
