Download Free A Comparison Of Three Methods Of Detecting Test Item Bias Book in PDF and EPUB Free Download. You can read online A Comparison Of Three Methods Of Detecting Test Item Bias and write the review.

In this book, the authors provide a cogent review of statistical and interpretive procedures that, in combination, can be used to reduce the likelihood that tests contain items that favor members of one gender, age, racial, or ethnic group over equally able members of another group, for reasons that are unrelated to the objectives and purposes of measurement. Such test items are said to be biased against the equally able members of the group that is not favored. The methods described and illustrated in this book have the potential to reducing the incidence of tests that are, in their construction, biased against members of one or more groups. These methods have the potential of controlling an important source of invalidity when test results are interpreted.
This book reviews the statistical procedures used to detect measurement bias. Measurement bias is examined from a general latent variable perspective so as to accommodate different forms of testing in a variety of contexts including cognitive or clinical variables, attitudes, personality dimensions, or emotional states. Measurement models that underlie psychometric practice are described, including their strengths and limitations. Practical strategies and examples for dealing with bias detection are provided throughout. The book begins with an introduction to the general topic, followed by a review of the measurement models used in psychometric theory. Emphasis is placed on latent variable models, with introductions to classical test theory, factor analysis, and item response theory, and the controversies associated with each, being provided. Measurement invariance and bias in the context of multiple populations is defined in chapter 3 followed by chapter 4 that describes the common factor model for continuous measures in multiple populations and its use in the investigation of factorial invariance. Identification problems in confirmatory factor analysis are examined along with estimation and fit evaluation and an example using WAIS-R data. The factor analysis model for discrete measures in multiple populations with an emphasis on the specification, identification, estimation, and fit evaluation issues is addressed in the next chapter. An MMPI item data example is provided. Chapter 6 reviews both dichotomous and polytomous item response scales emphasizing estimation methods and model fit evaluation. The use of models in item response theory in evaluating invariance across multiple populations is then described, including an example that uses data from a large-scale achievement test. Chapter 8 examines item bias evaluation methods that use observed scores to match individuals and provides an example that applies item response theory to data introduced earlier in the book. The book concludes with the implications of measurement bias for the use of tests in prediction in educational or employment settings. A valuable supplement for advanced courses on psychometrics, testing, measurement, assessment, latent variable modeling, and/or quantitative methods taught in departments of psychology and education, researchers faced with considering bias in measurement will also value this book.
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.
A unique, practical manual for identifying and analyzing item bias in standardized tests. Osterlind discusses five strategies for detecting bias: analysis of variance, transformed item difficulties, chi square, item characteristic curve, and distractor response. He covers specific hypotheses under test for each technique, as well as the capabilities and limitations of each strategy.
Educational Measurement has been the bible in its field since the first edition was published by ACE in 1951. The importance of this fourth edition of Educational Measurement is to extensively update and extend the topics treated in the previous three editions. As such, the fourth edition documents progress in the field and provides critical guidance to the efforts of new generations of researchers and practitioners. Edited by Robert Brennan and jointly sponsored by the American Council on Education (ACE) and the National Council on Measurement in Education, the fourth edition provides in-depth treatments of critical measurement topics, and the chapter authors are acknowledged experts in their respective fields. Educational measurement researchers and practitioners will find this text essential, and those interested in statistics, psychology, business, and economics should also find this work to be of very strong interest. Topics covered are divided into three subject areas: theory and general principles; construction, administration, and scoring; and applications. The first part of the book covers the topics of validation, reliability, item response theory, scaling and norming, linking and equating, test fairness, and cognitive psychology. Part two includes chapters on test development, test administration, performance assessment, setting performance standards, and technology in testing. The final section includes chapters on second language testing, testing for accountability in K-12 schools, standardized assessment of individual achievement in K-12 schools, higher education admissions testing, monitoring educational progress, licensure and certification testing, and legal and ethical issues.