Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument

Description: Many health care practitioners and researchers are aware of the need to employ factor analysis in order to develop more sensitive instruments for data collection. Unfortunately, factor analysis is not a unidimensional approach that is easily understood by even the most experienced of researchers. 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. Making Sense of Factor Analysis: The Use of Factor Analysis for Instrument Development in Health Care Research offers a practical method for developing tests, validating instruments and reporting outcomes through the use of factor analysis. To facilitate learning, the authors provide concrete testing examples, three appendices of additional information, and a glossary of key terms. Ideal for graduate level nursing students, this book is also an invaluable resource for health care researchers. 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. 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 Conclusions 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 References Index About the Authors

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