Abstract
Studying Ethnic Minority and Economically Disadvantaged Populations: Methodological Challenges and Best Practices. George P. Knight, Mark W. Roosa, & Adriana J. Umana-Taylor. Washington, DC: American Psychological Association. 2009. 224 pp. ISBN 1433804743. $69.95 cloth. Studying Ethnic Minority' and Economically Disadvantaged Populations is a guide for researchers who seek to study people of color and the poor. The authors note that the need for such a volume is evident in the proliferation of flawed research on specific ethnic and economic groups. To address this need, George P. Knight, Mark W. Roosa, and Adriana J. Umana-Taylor have written a slim and easy-to-read book with chapters on sampling, ethics, measurement equivalence, translation, and prevention. In selecting the methodological topics covered in the book, the authors have identified the most challenging aspects of such research and have compiled a primer on possible solutions to many challenges. Students who are beginning to conduct independent research will benefit from the book. Chapters begin with basic methodological principles, then include a discussion of the misapplications of those principles in studies of various ethnic groups and the poor, and then make recommendations for applying the principles with those populations. All the chapters emphasize the importance of critically evaluating cross-cultural research, which will likely lead to meaningful conversations about methodological issues and about how to think critically about published research if students and advisers read this book together. Therefore, it is a good book for introducing new researchers to the methodological issues of cross-cultural research. I found the authors' emphasis on measurement equivalence (Chapter 4) to be especially important because the transfer of psychometric properties across cultures and languages is often an overlooked facet of assessment. This is a good chapter for introducing students and experienced researchers to the issues of working with translated measures and interviews. The authors compare two statistical methods for evaluating measurement equivalence and recommend one procedure over the other. Readers who want more specifics about the procedures, which would be anyone who will actually run these analyses, can read of the authors' published work to see how they applied them to their own data (e.g., Nair, White, Knight, & Roosa, 2009). As such, the discussion of measurement equivalence is especially valuable because of the lack of attention the issue has received in much of the empirical literature on ethnic minorities and the poor. Although the book has much to offer students and beginning researchers, there were aspects that dampened my enthusiasm for it as a guide for more seasoned researchers. First, in addition to material that introduces the methodological issues in researching these populations, there are sections that assume that the researcher has either a high level of expertise or access to vast resources. Yet there seemed to be little attempt to connect the introductory sections with the advanced sections, which might lead to frustration among readers. For example, the chapter on measurement equivalence, which I still recommend, was both too basic and too advanced to be truly instructive. The first part of the chapter is a review of basic principles of psychometric theory, which should be familiar to most quantitative researchers. The second part is a sophisticated discussion of the benefits of nested hierarchical models in confirmatory factor analysis (CFA). There is little segue from the introductory material to the CFA material. There are similar issues in other chapters. A second major concern is that the authors have a tendency to rely too heavily on vague sources, as indicated in their use of phrases like some researchers feel . (p. 5) without citations to any specific researchers who feel that particular way. …
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