Assessing Measurement Invariance For Applied Research
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Author | : Craig S. Wells |
Publisher | : Cambridge University Press |
Total Pages | : 418 |
Release | : 2021-06-03 |
Genre | : Psychology |
ISBN | : 1108620744 |
This book focuses on the practical application of statistical techniques for assessing measurement invariance with less emphasis on theoretical development or exposition. Instead, it describes the methods using a pedagogical framework followed by extensive illustrations that demonstrate how to use software to analyze real data. The chapters illustrate the practical methods to assess measurement invariance and shows how to apply them to a range of data. The computer syntax and data sets used in this book are available for download here: people.umass.edu/cswells.
Author | : Rens Van De Schoot |
Publisher | : Frontiers Media SA |
Total Pages | : 219 |
Release | : 2015-10-05 |
Genre | : Psychology |
ISBN | : 288919650X |
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 | : Derya Evran |
Publisher | : |
Total Pages | : 97 |
Release | : 2012 |
Genre | : |
ISBN | : |
International assessments are often developed in one country and applied in other countries. Assessing the measurement invariance across countries is an important step in determining if valid conclusions can be drawn in these other countries and if valid comparisons can be made across countries under these circumstances. This study investigated measurement invariance, across two countries, of selected questions from the Programme for International Student Assessment 2009 student questionnaire. Turkey and United States were compared by using multiple group confirmatory factor analysis for scores on polytomous items. Specifically, the questions concerned enjoyment of reading, learning strategies, teacher student relations, and disciplinary climate, teachers\U+2019\ stimulation of reading engagement, and teachers'use of strategies. The results indicated that based on the chi-square goodness of fit test and root mean squared error of approximation, none of the models proposed in OECD (2012) adequately fit the data and all questions exhibited differential item functioning (DIF). However, based on the comparative fit index and the Tucker-Lewis index, models for questions, other than except learning strategies, fit the data. For these questions, results supported the fit of the strict factorial invariance model and indicated that the questions functioned similarly for students in Turkey and the United states. Thus the evidence for DIF was ambiguous except in regard to learning strategies. Under the assumption that the questions functioned similarly in Turkey and the United States, factor mean were compared across the two countries on questions other than learning strategies. According to the comparison, Turkish and American students significantly differed on all questions. The difference was large for enjoyment of reading, moderate for teachers' ruse of strategies, and small for the remaining questions.
Author | : Timothy A. Brown |
Publisher | : Guilford Publications |
Total Pages | : 482 |
Release | : 2015-01-07 |
Genre | : Science |
ISBN | : 146251779X |
This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...
Author | : |
Publisher | : |
Total Pages | : 0 |
Release | : 2015 |
Genre | : |
ISBN | : |
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 | : Luis Andres Alvarado |
Publisher | : |
Total Pages | : 85 |
Release | : 2013 |
Genre | : Analysis of covariance |
ISBN | : |
Dealing with measurement invariance has been an issue of concern in confirmatory factor analysis for many years. It is important to establish measurement invariance across groups so that instruments may be validly used in multiple groups for comparison of the mean or summative scores. Throughout the years, many studies have considered testing for measurement invariance in factor models. However, there have been no studies that assess measurement invariance when so-called testlets should be modeled in the factor analytic model. Testlets add nuisance covariation to the model which can interfere when trying to detect measurement invariance. In the past, models have been developed to compensate for any sort of added covariation within a model, such as the correlated error model, CT-C(M-1) model and random intercept factor model. However, can such models help detect measurement invariance in the presence of testlets? Additionally, which testlet model is most useful for detecting the true level of measurement invariance? Simulations help determine when in fact it is possible to compensate for this added testlet-based covariation and determine which method works best for various measurement invariance tests and scenarios. Generally, it is found that in some scenarios none of the models correctly identify the level of measurement invariance and, otherwise, the correlated error model is least prone to type I error.
Author | : Lucy R. Ford |
Publisher | : SAGE Publications Limited |
Total Pages | : 512 |
Release | : 2023-06-29 |
Genre | : Social Science |
ISBN | : 1529618622 |
The SAGE Handbook of Survey Development and Application provides a practical resource that researchers can go to for cutting-edge tools to ensure they are employing the best survey research techniques. This handbook not only covers the classic and innovational skills and approaches involved at every step of the survey research process, but also centres itself around applied, how-to guidance to aid readers in best practice. Chapters engage with a broad range of topics including sampling issues, approaches to establishment of measurement equivalence, and the use of online labour pools in survey development. With contributions from a global community of leading and emerging scholars across a wide variety of disciplines, this Handbook is focused on being applicable and accessible across the social sciences. Containing over 120 tables and figures, checklists and tutorial guides, The SAGE Handbook of Survey Development and Application will serve as a one stop resource for survey research. This handbook serves as a touchstone for a variety of fields such as Organizational Behavior, Industrial & Organizational Psychology, Management, Psychology, Educational Research, Marketing, Public Policy, and others. PART 1: Conceptual Issues and Operational Definition PART 2: Research Design Considerations PART 3: Item Development PART 4: Scale Improvement Methods PART 5: Data Collection PART 6: Data Management and Analysis PART 7: Research Production and Dissemination PART 8: Applications
Author | : Sumaya Laher |
Publisher | : Cambridge University Press |
Total Pages | : 397 |
Release | : 2022-08-11 |
Genre | : Business & Economics |
ISBN | : 1108485006 |
This book brings together expert research on the history of psychological assessment across the continents and spanning over 50 countries.
Author | : Timothy A. Brown |
Publisher | : Guilford Publications |
Total Pages | : 483 |
Release | : 2014-12-29 |
Genre | : Psychology |
ISBN | : 1462517811 |
With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website (www.guilford.com/brown3-materials) offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages.
Author | : Christof Wolf |
Publisher | : SAGE |
Total Pages | : 1065 |
Release | : 2016-07-11 |
Genre | : Social Science |
ISBN | : 1473959047 |
Survey Methodology is becoming a more structured field of research, deserving of more and more academic attention. The SAGE Handbook of Survey Methodology explores both the increasingly scientific endeavour of surveys and their growing complexity, as different data collection modes and information sources are combined. The handbook takes a global approach, with a team of international experts looking at local and national specificities, as well as problems of cross-national, comparative survey research. The chapters are organized into seven major sections, each of which represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of Survey Methodology is a landmark and essential tool for any scholar within the social sciences.