A First Course in Factor Analysis
A First Course in Factor Analysis

Author: Andrew L. Comrey

Publisher: Psychology Press

Published: 2013-11-12

Total Pages: 443

ISBN-13: 1317844076

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The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the mathematical basis of the most common factor analytic models and several methods used in factor analysis. On the application side, considerable attention is given to the extraction problem, the rotation problem, and the interpretation of factor analytic results. Hence, readers are given a background of understanding in the the theory underlying factor analysis and then taken through the steps in executing a proper analysis -- from the initial problem of design through choice of correlation coefficient, factor extraction, factor rotation, factor interpretation, and writing up results. This revised edition includes introductions to newer methods -- such as confirmatory factor analysis and structural equation modeling -- that have revolutionized factor analysis in recent years. To help remove some of the mystery underlying these newer, more complex methods, the introductory examples utilize EQS and LISREL. Updated material relating to the validation of the Comrey Personality Scales also has been added. Finally, program disks for running factor analyses on either an IBM-compatible PC or a mainframe with FORTRAN capabilities are available. The intended audience for this volume includes talented but mathematically unsophisticated advanced undergraduates, graduate students, and research workers seeking to acquire a basic understanding of the principles supporting factor analysis. Disks are available in 5.25" and 3.5" formats for both mainframe programs written in Fortran and IBM PCs and compatibles running a math co-processor.

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 ...

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.

A First Course in Structural Equation Modeling
A First Course in Structural Equation Modeling

Author: Tenko Raykov

Publisher: Routledge

Published: 2012-08-21

Total Pages: 248

ISBN-13: 1135600767

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In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one. Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner’s guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software. Highlights of the Second Edition include: • Review of latent change (growth) analysis models at an introductory level • Coverage of the popular Mplus program • Updated examples of LISREL and EQS • Downloadable resources that contains all of the text’s LISREL, EQS, and Mplus examples. A First Course in Structural Equation Modeling is intended as an introductory book for students and researchers in psychology, education, business, medicine, and other applied social, behavioral, and health sciences with limited or no previous exposure to SEM. A prerequisite of basic statistics through regression analysis is recommended. The book frequently draws parallels between SEM and regression, making this prior knowledge helpful.

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.

Best Practices in Quantitative Methods
Best Practices in Quantitative Methods

Author: Jason W. Osborne

Publisher: SAGE

Published: 2008

Total Pages: 609

ISBN-13: 1412940656

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The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Making Sense of Multivariate Data Analysis
Making Sense of Multivariate Data Analysis

Author: John Spicer

Publisher: SAGE

Published: 2005

Total Pages: 256

ISBN-13: 9781412904018

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A short introduction to the subject, this text is aimed at students & practitioners in the behavioural & social sciences. It offers a conceptual overview of the foundations of MDA & of a range of specific techniques including multiple regression, logistic regression & log-linear analysis.

Applied Factor Analysis in the Natural Sciences
Applied Factor Analysis in the Natural Sciences

Author: Richard A. Reyment

Publisher: Cambridge University Press

Published: 1996-09-28

Total Pages: 388

ISBN-13: 9780521575560

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This graduate-level text aims to introduce students of the natural sciences to the powerful technique of factor analysis and to provide them with the background necessary to be able to undertake analyses on their own. A thoroughly updated and expanded version of the authors' successful textbook on geological factor analysis, this book draws on examples from botany, zoology, ecology, and oceanography, as well as geology. Applied multivariate statistics has grown into a research area of almost unlimited potential in the natural sciences. The methods introduced in this book, such as classical principal components, principal component factor analysis, principal coordinate analysis, and correspondence analysis, can reduce masses of data to manageable and interpretable form. Q-mode and Q-R-mode methods are also presented. Special attention is given to methods of robust estimation and the identification of atypical and influential observations. Throughout the book, the emphasis is on application rather than theory.

A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling
A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling

Author: Larry Hatcher

Publisher: SAS Institute

Published: 2013-03-01

Total Pages: 444

ISBN-13: 1612903878

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Annotation Structural equation modeling (SEM) has become one of the most important statistical procedures in the social and behavioral sciences. This easy-to-understand guide makes SEM accessible to all userseven those whose training in statistics is limited or who have never used SAS. It gently guides users through the basics of using SAS and shows how to perform some of the most sophisticated data-analysis procedures used by researchers: exploratory factor analysis, path analysis, confirmatory factor analysis, and structural equation modeling. It shows how to perform analyses with user-friendly PROC CALIS, and offers solutions for problems often encountered in real-world research. This second edition contains new material on sample-size estimation for path analysis and structural equation modeling. In a single user-friendly volume, students and researchers will find all the information they need in order to master SAS basics before moving on to factor analysis, path analysis, and other advanced statistical procedures.