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Factor Analysis: Classic Edition 2nd edition [Kietas viršelis]

3.72/5 (18 ratings by Goodreads)
(Fuller Theological Seminary, USA)
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Comprehensive and comprehensible, this classic text covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and applying its use. This includes the theory as well as the empirical evaluations. The overall goal is to show readers how to use factor analysis in their substantive research by highlighting when the differences in mathematical procedures have a major impact on the substantive conclusions, when the differences are not relevant, and when factor analysis might not be the best procedure to use.

Although the original version was written years ago, the book maintains its relevance today by providing readers with a thorough understanding of the basic mathematical models so they can easily apply these models to their own research. Readers are presented with a very complete picture of the "inner workings" of these methods. The new Introduction highlights the remarkably few changes that the author would make if he were writing the book today.

An ideal text for courses on factor analysis or as a supplement for multivariate analysis, structural equation modeling, or advanced quantitative techniques taught in psychology, education, and other social and behavioral sciences, researchers who use these techniques also appreciate this book’s thorough review of the basic models. Prerequisites include a graduate level course on statistics and a basic understanding of algebra. Sections with an asterisk can be skipped entirely if preferred.

Recenzijos

"I have used Gorsuchs book "Factor Analysis" in my courses on exploratory factor analysis for the past ten years. I consider the book to be a classic in the field, and even though it was published in 1983, the book maintains its relevance. The author provides solid practical advice for researchers using factor analytic techniques that is just as important today as it was when the book was written. In addition to his practical advice, Gorsuch provides the mathematical underpinnings of factor analytic techniques so that students and applied researchers can truly understand the "inner workings" of these methods. In my view, his book is the ideal combination of technical rigor and practical advice, which results in a comprehensive text that is accessible to applied researchers." - Deborah L. Bandalos, James Madison University, USA

"Factor analysis is a widely used statistical technique across many disciplines. Its use will not decrease any time soon. Yet, the knowledge of its basics, as it was developed in the 60s and 70s can only be found in classic books. A reprint of Gorsuchs book of factor analysis is timely and it will be well received." - Albert Maydeu-Olivares, University of Barcelona, Spain

Gorsuch is a staple for anyone interested in an informative and accessible presentation of factor analysis (FA).The book presents the mathematics of FA in an applied and comprehensible style that is understandable to most readers. The material presented is still essential for current teaching, learning, and application. Anyone interested in FA will readily find this book an instructive classic by a well-respected expert." - Lisa L. Harlow, University of Rhode Island, USA

Preface xiii
Preface to the First Edition xv
Introduction to the Classic Edition xviii
1 Introduction 1(14)
1.1 Science and factor analysis
1(4)
1.2 Elementary procedures for factoring
5(4)
1.3 Examples
9(6)
2 Basic Factor Models 15(24)
2.1 Multivariate linear models and factor analysis
15(6)
2.2 The full component model
21(6)
2.3 The common factor model
27(7)
2.4 Correlated and uncorrelated factor models
34(2)
2.5 Which factor-analytic model?
36(3)
3 Matrix Algebra and Factor Analysis 39(21)
3.1 Matrix definitions and notation
39(5)
3.2 Matrix operations
44(7)
3.3 Definitional equations in matrix algebra form
51(2)
3.4 The full component model expressed in matrix algebra
53(2)
3.5 The common factor model in matrix algebra
55(3)
3.6 Uncorrelated factor models and matrix algebra
58(2)
4 Geometric Representation of Factor Models 60(17)
4.1 Representing variables and factors geometrically
61(9)
4.2 The uncorrelated (orthogonal) component model
70(3)
4.3 The correlated (oblique) component model
73(3)
4.4 Common factor models
76(1)
5 Diagonal and Multiple-group Analysis 77(23)
5.1 Diagonal analysis
78(7)
5.2 Multiple-group factor analysis
85(8)
5.3 Applications of diagonal and multiple-group factor analysis
93(7)
6 Principal Factor Solutions 100(35)
6.1 Characteristics of principal factor methods
101(4)
6.2 Principal components
105(4)
6.3 Communality estimation and principal axes
109(10)
6.4 Image analysis
119(4)
6.5 Other related procedures
123(3)
6.6 Nonlinear and nonmetric factor analysis
126(2)
6.7 Applications for principal factors
128(1)
6.8 A comparison of factor extraction procedures
129(6)
7 Confirmatory Maximum Likelihood Solutions 135(16)
7.1 The maximum likelihood concept
135(2)
7.2 Confirmatory maximum likelihood factor analysis
137(4)
7.3 Applications
141(8)
7.4 Hypothesis testing by maximum likelihood and multiple-group procedures
149(2)
8 Determining the Number of Factors 151(35)
8.1 Adequacy of the fit of the model to the data
152(4)
8.2 Statistical approaches to the number of factors
156(9)
8.3 Mathematical approaches to the number of factors
165(9)
8.4 Extracting the nontrivial factors
174(6)
8.5 The search for the proper number of factors
180(6)
9 Rotation and Interpretation of Factors 186(39)
9.1 Principles for guiding the rotation of factors
187(6)
9.2 Orthogonal rotation for simple structure
193(6)
9.3 Oblique analytic rotation for simple structure
199(9)
9.4 Comparing alternative solutions
208(9)
9.5 Interpreting factors
217(8)
10 Rotation 225(28)
10.1 Algebraic principles of rotation
226(4)
10.2 Rotating visually
230(10)
10.3 Orthoblique solutions
240(5)
10.4 Nonsimple structure rotation
245(5)
10.5 Extension analysis
250(3)
11 Higher-order Factors 253(19)
11.1 Interpretation of higher-order factors
254(2)
11.2 Extracting higher-order factors
256(4)
11.3 Relationship of variables to higher-order factors
260(9)
11.4 Usefulness of higher-order factors
269(3)
12 Factor Scores 272(21)
12.1 Procedures for computing factor scores
273(8)
12.2 Approximation procedures for factor scores
281(4)
12.3 Cluster analysis of individuals: typological scoring
285(2)
12.4 Evaluating the factor scores
287(4)
12.5 Selecting among procedures
291(2)
13 Relating Factors Across Studies 293(14)
13.1 Information useful in relating factors
294(2)
13.2 Same individuals and variables but different procedures
296(1)
13.3 Same individuals but different variables
297(1)
13.4 Same variables but different individuals (Rvv, Svf, and Wvf available)
298(2)
13.5 Same variables but different individuals (Rvv, Svf, and Wvf unavailable)
300(5)
13.6 Different variables and different individuals
305(1)
13.7 Matching factors
305(2)
14 Data Transformations and Indices of Association 307(20)
14.1 Noncontinuous data
307(6)
14.2 Effects of transformations
313(7)
14.3 Indices of association
320(7)
15 Two- and Three-mode Factor Analysis 327(19)
15.1 Two-mode factor analysis 328.
15.2 Three-mode factor analysis
336(10)
16 The Replication and Invariance of Factors 346(23)
16.1 The replication of factors across random samples of individuals
346(6)
16.2 The invariance of factors
352(17)
17 Factor Analysis as a Research Technique 369(20)
17.1 Operationalization of constructs
369(9)
17.2 Factor analysis of independent and dependent variables
378(7)
17.3 Using factor analysis to suggest new leads for future research
385(2)
17.4 Other uses of factor analysis
387(1)
17.5 Concluding note
388(1)
18 Epilogue 389(13)
18.1 Criticisms of present factor-analytic practices
389(3)
18.2 Recommended procedures for selected research designs
392(7)
18.3 The future of factor analysis
399(3)
Appendix A Data for Examples 402(3)
Appendix B.1 Computer Programs for Factor Analysis 405(2)
Appendix B.2 Accuracy of Computer Processing 407(5)
References 412(20)
Author Index 432(5)
Subject Index 437
Richard L. Gorsuch is Senior Professor of Psychology at the Fuller Theological Seminary. He is known for his book Factor Analysis (1983), and for the development of the software program UniMult.