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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.
The field of education has experienced extraordinary technological, societal, and institutional change in recent years, making it one of the most fascinating yet complex fields of study in social science. Unequalled in its combination of authoritative scholarship and comprehensive coverage, International Encyclopedia of Education, Third Edition succeeds two highly successful previous editions (1985, 1994) in aiming to encapsulate research in this vibrant field for the twenty-first century reader. Under development for five years, this work encompasses over 1,000 articles across 24 individual areas of coverage, and is expected to become the dominant resource in the field. Education is a multidisciplinary and international field drawing on a wide range of social sciences and humanities disciplines, and this new edition comprehensively matches this diversity. The diverse background and multidisciplinary subject coverage of the Editorial Board ensure a balanced and objective academic framework, with 1,500 contributors representing over 100 countries, capturing a complete portrait of this evolving field. A totally new work, revamped with a wholly new editorial board, structure and brand-new list of meta-sections and articles Developed by an international panel of editors and authors drawn from senior academia Web-enhanced with supplementary multimedia audio and video files, hotlinked to relevant references and sources for further study Incorporates ca. 1,350 articles, with timely coverage of such topics as technology and learning, demography and social change, globalization, and adult learning, to name a few Offers two content delivery options - print and online - the latter of which provides anytime, anywhere access for multiple users and superior search functionality via ScienceDirect, as well as multimedia content, including audio and video files
Persistent differences between racial groups on standardized aptitude test scores have suggested the potential for unfair discrimination against members of different racial and ethnic subpopulations. Because many occupational and educational opportunities are affected by mental test scores, the issue of test bias has consequences for many people in our society. Of the many statistical techniques proposed for detecting biased items there appears to be a preference for techniques based on a latent trait or item response theory (IRT) because sample estimates of population item parameters are invariant. This advantage occurs because, when the IRT model is valid, item parameters are invariant with respect to subpopulation ability distributions. This study concerns the effects of test multidimensionality on recommended item bias statistics. Simulation data samples (N=1,000 each) on a 50 item test were generated using a factor model described and used by Drasgow and Parsons. Subpopulation differences on common factors led to item bias that was identified to some extent by both chi-square and IRT bias indices. The signed indices were especially effective in distinguishing biased items from unbiased items. However, the use of either the signed chi-square or signed IRT index in multidimensional data clearly requires a priori knowledge of which subpopulation is at a disadvantage. This unexpected finding suggests further study of the properties of signed indices as well as a reevaluation of previous simulation research that has appeared to support their validity.
The second edition of this comprehensive volume presents methods for nonverbal assessment of diverse individuals, such as persons with speech or hearing deficits, limited English skills, or emotional problems. Chapters provide a contemporary context for nonverbal evaluations, accompanied by descriptions of best practices in detecting bias in cognitive tests, multicultural assessment, cross-battery assessment of nonverbal cognitive ability, and psychological and physiological influences on assessment. The book discusses nonverbal assessment of cognition and intelligence as well as related domains, such as academic skills, neurocognitive functioning, personality, and behavior issues. Guidelines for using common nonverbal assessment tools and strategies feature the most up-to-date information on administration and scoring, psychometric properties, and strengths and limitations. Best practices for testing diverse children and adults and using reliable, valid, and fair assessment instruments are emphasized throughout the book. Featured instruments in the Handbook include: The Universal Nonverbal Intelligence Test, Second Edition (UNIT2). The newest version of the Leiter International Performance Scale (Leiter-3). The Wechsler Nonverbal Scale of Ability (WNV). The Comprehensive Test of Nonverbal Intelligence, Second Edition (CTONI-2). The Test of Nonverbal Intelligence. The General Ability Measure for Adults (GAMA). The Second Edition of the Handbook of Nonverbal Assessment is a must-have resource for researchers and graduate students in school and clinical child psychology, speech and language pathology, educational technology, social work, and related disciplines as well as clinicians, professionals, and in-service educators of diverse students.
Quantifying the User Experience: Practical Statistics for User Research, Second Edition, provides practitioners and researchers with the information they need to confidently quantify, qualify, and justify their data. The book presents a practical guide on how to use statistics to solve common quantitative problems that arise in user research. It addresses questions users face every day, including, Is the current product more usable than our competition? Can we be sure at least 70% of users can complete the task on their first attempt? How long will it take users to purchase products on the website? This book provides a foundation for statistical theories and the best practices needed to apply them. The authors draw on decades of statistical literature from human factors, industrial engineering, and psychology, as well as their own published research, providing both concrete solutions (Excel formulas and links to their own web-calculators), along with an engaging discussion on the statistical reasons why tests work and how to effectively communicate results. Throughout this new edition, users will find updates on standardized usability questionnaires, a new chapter on general linear modeling (correlation, regression, and analysis of variance), with updated examples and case studies throughout. Completely updated to provide practical guidance on solving usability testing problems with statistics for any project, including those using Six Sigma practices Includes new and revised information on standardized usability questionnaires Includes a completely new chapter introducing correlation, regression, and analysis of variance Shows practitioners which test to use, why they work, and best practices for application, along with easy-to-use Excel formulas and web-calculators for analyzing data Recommends ways for researchers and practitioners to communicate results to stakeholders in plain English