Exploratory Factor Analysis

Exploratory Factor Analysis

Author: W. Holmes Finch

Publisher: SAGE Publications

Published: 2019-09-05

Total Pages: 140

ISBN-13: 1544339879

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A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation in exploratory factor analysis (EFA), which along with confirmatory factor analysis, represents one of the two major strands in this field. The book lays out the mathematical foundations of EFA; explores the range of methods for extracting the initial factor structure; explains factor rotation; and outlines the methods for determining the number of factors to retain in EFA. The concluding chapter addresses a number of other key issues in EFA, such as determining the appropriate sample size for a given research problem, and the handling of missing data. It also offers brief introductions to exploratory structural equation modeling, and multilevel models for EFA. Example computer code, and the annotated output for all of the examples included in the text are available on an accompanying website.


Introduction to Factor Analysis

Introduction to Factor Analysis

Author: Jae-On Kim

Publisher: SAGE

Published: 1978-11

Total Pages: 84

ISBN-13: 9780803911659

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Describes the mathematical and logical foundations at a level that does not presume advanced mathematical or statistical skills. It illustrates how to do factor analysis with several of the more popular packaged computer programs.


Confirmatory Factor Analysis for Applied Research, Second Edition

Confirmatory Factor Analysis for Applied Research, Second Edition

Author: Timothy A. Brown

Publisher: Guilford Publications

Published: 2015-01-07

Total Pages: 482

ISBN-13: 146251779X

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This accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA) for its emphasis on practical and conceptual aspects rather than mathematics or formulas. Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities ...


An Easy Guide to Factor Analysis

An Easy Guide to Factor Analysis

Author: Paul Kline

Publisher: Routledge

Published: 2014-02-25

Total Pages: 203

ISBN-13: 1317725603

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Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, and concludes with a discussion of the use of the technique with various examples. An Easy Guide to Factor Analysis is the clearest, most comprehensible introduction to factor analysis for students. All those who need to use statistics in psychology and the social sciences will find it invaluable. Paul Kline is Professor of Psychometrics at the University of Exeter. He has been using and teaching factor analysis for thirty years. His previous books include Intelligence: the psychometric view (Routledge 1990) and The Handbook of Psychological Testing (Routledge 1992).


Exploratory Factor Analysis

Exploratory Factor Analysis

Author: Leandre R. Fabrigar

Publisher: Oxford University Press

Published: 2012-01-12

Total Pages: 170

ISBN-13: 0199734178

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This book provides a non-mathematical introduction to the theory and application of Exploratory Factor Analysis. Among the issues discussed are the use of confirmatory versus exploratory factor analysis, the use of principal components analysis versus common factor analysis, and procedures for determining the appropriate number of factors.


Factor Analysis and Related Methods

Factor Analysis and Related Methods

Author: Roderick P. McDonald

Publisher: Psychology Press

Published: 1985

Total Pages: 280

ISBN-13: 9780898593884

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First Published in 1985. Routledge is an imprint of Taylor & Francis, an informa company.


Factor Analysis

Factor Analysis

Author: Jae-On Kim

Publisher: SAGE

Published: 1978-11

Total Pages: 92

ISBN-13: 9780803911666

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Describes various commonly used methods of initial factoring and factor rotation. In addition to a full discussion of exploratory factor analysis, confirmatory factor analysis and various methods of constructing factor scales are also presented.


Latent Variable Models

Latent Variable Models

Author: John C. Loehlin

Publisher: Psychology Press

Published: 2004-05-20

Total Pages: 303

ISBN-13: 1135614342

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This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between path analysis, factor analysis, and structural equation modeling more easily. A few sections of the book make use of elementary matrix algebra. An appendix on the topic is provided for those who need a review. The author maintains an informal style so as to increase the book's accessibility. Notes at the end of each chapter provide some of the more technical details. The book is not tied to a particular computer program, but special attention is paid to LISREL, EQS, AMOS, and Mx. New in the fourth edition of Latent Variable Models: *a data CD that features the correlation and covariance matrices used in the exercises; *new sections on missing data, non-normality, mediation, factorial invariance, and automating the construction of path diagrams; and *reorganization of chapters 3-7 to enhance the flow of the book and its flexibility for teaching. Intended for advanced students and researchers in the areas of social, educational, clinical, industrial, consumer, personality, and developmental psychology, sociology, political science, and marketing, some prior familiarity with correlation and regression is helpful.


Introduction to Statistics in Psychology

Introduction to Statistics in Psychology

Author: Dennis Howitt

Publisher: Pearson Education

Published: 2008

Total Pages: 564

ISBN-13: 9780132051613

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Introduction to Statistics in Psychology4th edition is the complete guide to statistics for psychology students. Its range is exceptional in order to meet student needs throughout their undergraduate degree and beyond. By keeping to simple mathematics, step by step explanations of all the important statistical concepts, tests and procedures ensure that students understand data analysis properly. Pedagogical features such as ‘research design issues’, ‘calculations’ and the advice boxes help structure study into manageable sections whilst the overview and key points help with revision. Plus this 4th edition includes even more examples to bring to life how different statistical tests can be used in different areas of psychology.


Factor Analysis

Factor Analysis

Author: Richard L. Gorsuch

Publisher: Routledge

Published: 2014-11-27

Total Pages: 465

ISBN-13: 1317564898

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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.