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Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research 1st Edition

5.0 out of 5 stars 12 customer reviews
ISBN-13: 978-0761919506
ISBN-10: 0761919503
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Editorial Reviews

About the Author

Marjorie A. Pett, MStat, DSW, is a Research Professor in the College of Nursing at the University of Utah, Salt Lake City, Utah, having been on the faculty since 1980. By her own admission, she is a “collector” of academic degrees: BA (Brown University), MS in sociology (University of Stockholm, Sweden), MSW (Smith College), DSW (University of Utah), and MStat (Biostatistics) (University of Utah).

Dr. Pett has a strong commitment to facilitating the practical application of statistics in the social, behavioral, and biological sciences, especially among practitioners in health care settings. She has designed and taught graduate courses to students from a variety of disciplines at the beginning and advanced levels, including research design and data management, parametric and nonparametric statistics, biostatistics, multivariate statistics, instrument development, and factor analysis. She has tried to approach the teaching of statistics with humor and from a clinician’s perspective and has been the recipient of several distinguished teaching awards both at the College and University levels.

Her most recent research interests include the development of client-centered assessment tools and interventions to evaluate and enhance health-related quality of life (HRQoL) for persons with intellectual disabilities. She is the author of numerous research articles and chapters, and is an author of the Sage publication, Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research.

When not engaged in research, writing, or teaching, Marge is a (now retired) state soccer referee, devotee of tennis, an avid (high handicap) golfer, student of Italian and French, reader of mystery novels, grandmother to three, mother to two, and wife to (only) one. 



Dr John Sullivan has been a professor of management for over 26 years at San Francisco State University. His specialty is HR strategy and designing world class HR systems and tools for Fortune 200 firms. He has worked with over 200 different businesses and organizations in more than 30 countries around the world as a speaker or advisor. He has written a weekly column for ERE for over eleven years. Overall, he has written ten books, dozens of white papers and over 700 articles. He was the chief talent officer for Agilent (the 40,000+ employee HP spin off). He has appeared on the CBS and ABC national nightly news, CNN and in various publications including Fortune, the Economist, CIO, BusinessWeek, the WSJ, the Washington Post, Money, Time and every major HR magazine. Fast company called him the Michael Jordan of hiring. He was listed among the 40 most influential people in HR. Tom Peters cites and utilizes his work in his latest book Re-Imagine.
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Product Details

  • Paperback: 368 pages
  • Publisher: SAGE Publications, Inc; 1 edition (March 21, 2003)
  • Language: English
  • ISBN-10: 0761919503
  • ISBN-13: 978-0761919506
  • Product Dimensions: 6 x 0.8 x 9 inches
  • Shipping Weight: 1 pounds (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (12 customer reviews)
  • Amazon Best Sellers Rank: #436,593 in Books (See Top 100 in Books)

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Top Customer Reviews

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This is a great book for those who are new to factor analysis. Although written from the perspective of a health care researcher, it's easily accessible to folks in other disciplines (I'm in educational leadership). I especially appreciated the step-by-step process for doing factor analysis from beginning to end, along with thorough explanations of various choices (and why you'd make them) along the way.
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Many of us who have used factor analysis had only a vague notion of what we were doing, namely trying to reduce a large number of items into a smaller, less unwieldy, more readily interpretable set of variables. With user-friendly software such as SPSS, the mechanics -- entering items, extracting factors, rotation of factors, saving factor scores if needed, and calculating reliability coefficients -- are sufficiently obvious to permit rough and ready, sometimes quite useful factor solutions that provide insights that otherwise would not have been available.

Without studying factor analysis as such, however, such quick and dirty applications often yield misleading results, something that anonymous reviewers of submitted manuscripts will be only too happy to acerbically explain. In my own work, I stared off routinely using principal components analysis, the SPSS default option for factor analysis, but had no notion that principal components analysis and factor analysis in its various forms are mathematically distinct. Principal components uses all three sources of variance -- shared, random, and error variance in formulating components, while factor analysis uses only shared variance. One common outcome is that principal components will typically yield a misleadingly clear-cut solution, while factor analysis rightly yields a solution that requires more interpretative effort.

Furthermore, when trying to reduce a comparatively large number of items to a small set of themes or variables, we get our most informative results when the analysis is limited to shared variance. Thus, while principal components has its uses, one of the many forms of factor analysis, say alpha factoring, is usually better suited to the task at hand.
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This is the best book I've found on factor analysis - I am not mathematically inclined, but I do want to understand "the sense" of factor analysis. This book is detailed, clear, with concise summaries as well as detailed explanations of the matrix algebra and math of factor analyses. It contains clear and useful diagrams. I have checked out several other books on factor analysis - this is the one that finally explained the subject to me.
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I have used this book for over two years now. I keep it in my small "library" of books and articles on factor analysis. I am not a statistician, but I do use factor analysis regularly in my research. The authors provide as good an explanation of the process and how to use the method as any writers. The reason I give it a top rating is its attention to practical issues that the statistician would not consider but are essential in the practical application of factor analysis to understanding data. I recommend adding the book to your library!
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My professor says it's a little outdated, but I had only a vague understanding of factor analysis before reading the book and after, I was able to correctly conduct factor analysis for work. Excellent text. Too bad it's a little outdated.
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I am a PH student at Universdad Nacional de Colombia (Engineering Faculty). The Pett et al.`s book presents a detail explanation (focuses on "HOW") of the procedure involved to make factor analysis (FA). The authors made a great effort in writing a book understandable to those inexperienced researchers with no strong formation in statistics. The only thing that I criticize is that this wonderful book was written emphasizing on the "how" with less focus on the "why" and very little treatment on the explanation and foundations of the descriptive and statistical approach of FA.
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