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

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

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Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research presents a straightforward explanation of the complex statistical procedures involved in factor analysis. Authors Marjorie A. Pett, Nancy M. Lackey, and John J. Sullivan provide a step-by-step approach to analyzing data using statistical computer packages like SPSS and SAS. Emphasizing the interrelationship between factor analysis and test construction, the authors examine numerous practical and theoretical decisions that must be made to efficiently run and accurately interpret the outcomes of these sophisticated computer programs.

Product Details

ISBN-13: 9780761919506
Publisher: SAGE Publications
Publication date: 03/21/2003
Edition description: New Edition
Pages: 368
Sales rank: 426,233
Product dimensions: 6.00(w) x 9.00(h) x 0.76(d)

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 (HRQo L) 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, Business Week, 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.

Table of Contents

1. An Overview of Factor Analysis
Characteristics of Factor Analysis
Exploratory Vs. Confirmatory Factor Analysis
Assumptions of Exploratory Factor Analysis
Historical Developments of Factor Analysis
Uses of Factor Analysis in Health Care Research
Decision-Making Process in Exploratory Factor Analysis
2. Designing and Testing the Instrument
Types of Measurement and Frameworks
The Use of Latent Variables in Instrument Development
Identifying Empirical Indicators of Latent Variables
Using Qualitative Research Methods to Identify Empirical Indicators
Additional Qualitative Approaches to Identifying Empirical Indicators
Development of the Instrument
Scoring the Instrument
Pilot Testing the Instrument
Determining the Number of Subjects
3. Assessing the Characteristics of Matrices
Characteristics and Types of Matrices
Tests of Matrices
Review of the Process
4. Extracting the Initial Factors
Evaluating the Correlation Matrix
Sources of Variance in Factor Analysis Models
Determining the Factor Extraction Method
Selecting the Number of Factors to Retain
Comparing the Two-Factor Solution Using PCA and PAF
5. Rotating the Factors
Achieving a Simple Structure
Types of Rotations
Mapping Factors in Geometric Space
Orthogonal Rotations
Oblique Rotations
Comparing the Orthogonal and Oblique Solutions
Advantages and Disadvantages of the Oblique Solution
Choosing Between Orthogonal and Oblique Rotations
Summary of the Process of Rotations
6. Evaluating and Refining the Factors
Evaluating and Refining the Factors
Assessing the Reliability of an Instrument
Evaluating the Internal Consistency of an Instrument
Estimating the Effects on Reliability of Increasing or Decreasing Items
Cronbach's Coefficient Alpha
Assessing Reliability Using Cronbach's Alpha: A Computer Example
Two Additional Reliability Estimates: Temporal Stability and Equivalence
7. Interpreting Factors and Generating Factor Scores
Interpreting the Factors
Naming the Factors
Interpreting and Naming the Four Factors on the CGTS Scale
Determining Composite Factor Scores
8. Reporting and Replicating the Results
When to Report the Results
What to Include in the Report
An Exemplar of a Published Report
Replicating the Factors in Other Studies
Appendix A: Concerns About Genetic Testing Scale
Appendix B: SAS Commands and Generate Output
Appendix C: Output for 20-item CGTS Scale
Appendix D: Tables for the Chi-Square and Normal Distributions
Appendix E: Unraveling the Mystery of Principal Component Extraction
About the Authors

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