Assessing Measurement Invariance in Questionnaires Within Latent Trait Models Using Item Response Theory PDF Download

Author: Alberto Maydeu Olivares
Publisher:
ISBN:
Category :
Languages : en
Pages : 24

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Author: Albert Maydeu-Olivares
Publisher:
ISBN:
Category :
Languages : en
Pages : 24

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Author: Rens Van De Schoot
Publisher: Frontiers Media SA
ISBN: 288919650X
Category : Psychology
Languages : en
Pages : 219

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Book Description
Multi-item surveys are frequently used to study scores on latent factors, like human values, attitudes and behavior. Such studies often include a comparison, between specific groups of individuals, either at one or multiple points in time. If such latent factor means are to be meaningfully compared, the measurement structures including the latent factor and their survey items should be stable across groups and/or over time, that is ‘invariant’. Recent developments in statistics have provided new analytical tools for assessing measurement invariance (MI). The aim of this special issue is to provide a forum for a discussion of MI, covering some crucial ‘themes’: (1) ways to assess and deal with measurement non-invariance; (2) Bayesian and IRT methods employing the concept of approximate measurement invariance; and (3) new or adjusted approaches for testing MI to fit increasingly complex statistical models and specific characteristics of survey data. The special issue started with a kick-off meeting where all potential contributors shared ideas on potential papers. This expert workshop was organized at Utrecht University in The Netherlands and was funded by the Netherlands Organization for Scientific Research (NWO-VENI-451-11-008). After the kick-off meeting the authors submitted their papers, all of which were reviewed by experts in the field. The papers in the eBook are listed in alphabetical order, but in the editorial the papers are introduced thematically. Although it is impossible to cover all areas of relevant research in the field of MI, papers in this eBook provide insight on important aspects of measurement invariance. We hope that the discussions included in this special issue will stimulate further research on MI and facilitate further discussions to support the understanding of the role of MI in multi-item surveys.

Author: Steven P. Reise
Publisher: Routledge
ISBN: 131756569X
Category : Psychology
Languages : en
Pages : 710

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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: Craig S. Wells
Publisher: Cambridge University Press
ISBN: 1108485227
Category : Education
Languages : en
Pages : 417

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This user-friendly guide illustrates how to assess measurement invariance using computer programs, statistical methods, and real data.

Author: Weicong Lyu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Item response theory (IRT) is currently the dominant methodological paradigm in educational and psychological measurement. IRT models are based on assumptions about the relationship between latent traits and observed responses, so the accuracy of the methodology depends heavily on the reasonableness of these assumptions. This dissertation consists of three studies, all of which focus on different scenarios where existing IRT models do not agree closely with reality and thus may provide misleading or insufficient characterizations of measurement phenomena. In the first study, I discuss anchoring, the tendency for respondents to select categories near the rating category used for the immediately preceding item in self-report rating scale assessments. I propose a psychometric model based on a multidimensional nominal model for response style that also simultaneously accommodates a respondent-level anchoring tendency. This model is applied to a real dataset measuring extraversion, and empirical results support attending to both anchoring and midpoint response styles as ways of assessing respondent engagement. In the second study, I examine the simultaneous relevance of content trait level and response styles as predictive factors of response time on noncognitive assessments, and the potential for omitted variable bias when ignoring either factor. Using response time data from several noncognitive assessments, I demonstrate how a multilevel model leads to consistent findings that support the simultaneous relevance of both factors. The average effects of response style consistently emerge as stronger, although also show greater respondent-level variability, than those of content traits. In the third study, test items whose scores reflect sequential or IRTree modeling outcomes are considered. For such items, I argue that item specific factors, although not empirically measurable, are often present across stages of the same item. A conceptual model that incorporates such factors is proposed and used to demonstrate how they create ambiguity in the interpretations of item and person parameters beyond the first stage. Various empirical applications show patterns of violations of item parameter invariance across stages that are highly suggestive of item specific factors. These studies reflect some recent advances in IRT modeling applied to practical issues, which hopefully will benefit both methodologists and practitioners.

Author: M.D. Reckase
Publisher: Springer Science & Business Media
ISBN: 0387899766
Category : Social Science
Languages : en
Pages : 355

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First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing

Author: Rebecca Holman
Publisher:
ISBN: 9090191232
Category :
Languages : en
Pages : 160

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Author: Ronald K. Hambleton
Publisher: Springer Science & Business Media
ISBN: 9401719888
Category : Education
Languages : en
Pages : 340

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Book Description
In the decade of the 1970s, item response theory became the dominant topic for study by measurement specialists. But, the genesis of item response theory (IRT) can be traced back to the mid-thirties and early forties. In fact, the term "Item Characteristic Curve," which is one of the main IRT concepts, can be attributed to Ledyard Tucker in 1946. Despite these early research efforts, interest in item response theory lay dormant until the late 1960s and took a backseat to the emerging development of strong true score theory. While true score theory developed rapidly and drew the attention of leading psychometricians, the problems and weaknesses inherent in its formulation began to raise concerns. Such problems as the lack of invariance of item parameters across examinee groups, and the inadequacy of classical test procedures to detect item bias or to provide a sound basis for measurement in "tailored testing," gave rise to a resurgence of interest in item response theory. Impetus for the development of item response theory as we now know it was provided by Frederic M. Lord through his pioneering works (Lord, 1952; 1953a, 1953b). The progress in the fifties was painstakingly slow due to the mathematical complexity of the topic and the nonexistence of computer programs.

Author: Frank B. Baker
Publisher: Springer
ISBN: 3319542052
Category : Social Science
Languages : en
Pages : 177

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Book Description
This graduate-level textbook is a tutorial for item response theory that covers both the basics of item response theory and the use of R for preparing graphical presentation in writings about the theory. Item response theory has become one of the most powerful tools used in test construction, yet one of the barriers to learning and applying it is the considerable amount of sophisticated computational effort required to illustrate even the simplest concepts. This text provides the reader access to the basic concepts of item response theory freed of the tedious underlying calculations. It is intended for those who possess limited knowledge of educational measurement and psychometrics. Rather than presenting the full scope of item response theory, this textbook is concise and practical and presents basic concepts without becoming enmeshed in underlying mathematical and computational complexities. Clearly written text and succinct R code allow anyone familiar with statistical concepts to explore and apply item response theory in a practical way. In addition to students of educational measurement, this text will be valuable to measurement specialists working in testing programs at any level and who need an understanding of item response theory in order to evaluate its potential in their settings.