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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 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
Test fairness is a moral imperative for both the makers and the users of tests. This book focuses on methods for detecting test items that function differently for different groups of examinees and on using this information to improve tests. Of interest to all testing and measurement specialists, it examines modern techniques used routinely to insure test fairness. Three of these relevant to the book's contents are: * detailed reviews of test items by subject matter experts and members of the major subgroups in society (gender, ethnic, and linguistic) that will be represented in the examinee population * comparisons of the predictive validity of the test done separately for each one of the major subgroups of examinees * extensive statistical analyses of the relative performance of major subgroups of examinees on individual test items.
By using familiar concepts from classical measurement methods and basic statistics, this book introduces the basics of item response theory (IRT) and explains the application of IRT methods to problems in test construction, identification of potentially biased test items, test equating and computerized-adaptive testing. The book also includes a thorough discussion of alternative procedures for estimating IRT parameters and concludes with an exploration of new directions in IRT research and development.
First thorough treatment of multidimensional item response theory Description of methods is supported by numerous practical examples Describes procedures for multidimensional computerized adaptive testing