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Foundations of Factor Analysis

Foundations of Factor Analysis
Author: Stanley A Mulaik
Publisher: CRC Press
Total Pages: 550
Release: 2009-09-25
Genre: Mathematics
ISBN: 1420099817

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Providing a practical, thorough understanding of how factor analysis works, Foundations of Factor Analysis, Second Edition discusses the assumptions underlying the equations and procedures of this method. It also explains the options in commercial computer programs for performing factor analysis and structural equation modeling. This long-awaited e


Confirmatory Factor Analysis for Applied Research, Second Edition

Confirmatory Factor Analysis for Applied Research, Second Edition
Author: Timothy A. Brown
Publisher: Guilford Publications
Total Pages: 482
Release: 2015-01-07
Genre: Science
ISBN: 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 ...


Making Sense of Factor Analysis

Making Sense of Factor Analysis
Author: Marjorie A. Pett
Publisher: SAGE
Total Pages: 369
Release: 2003-03-21
Genre: Mathematics
ISBN: 0761919503

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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. This accessible volume will help both novice and experienced health care professionals to Increase their knowledge of the use of factor analysis in health care research Understand journal articles that report the use of factor analysis in test construction and instrument development Create new data collection instruments Examine the reliability and structure of existing health care instruments Interpret and report computer-generated output from a factor analysis run 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.


Introduction to Factor Analysis

Introduction to Factor Analysis
Author: Jae-On Kim
Publisher: SAGE
Total Pages: 84
Release: 1978-11
Genre: Mathematics
ISBN: 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.


Exploratory Factor Analysis

Exploratory Factor Analysis
Author: W. Holmes Finch
Publisher: SAGE Publications
Total Pages: 133
Release: 2019-09-05
Genre: Social Science
ISBN: 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.


Factor Analysis at 100

Factor Analysis at 100
Author: Robert Cudeck
Publisher: Routledge
Total Pages: 401
Release: 2007-03-06
Genre: Business & Economics
ISBN: 113559404X

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Factor analysis is one of the success stories of statistics in the social sciences. The reason for its wide appeal is that it provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. Because of its importance, a conference was held to mark the centennial of the publication of Charles Spearman's seminal 1904 article which introduced the major elements of this invaluable statistical tool. This book evolved from that conference. It provides a retrospective look at major issues and developments as well as a prospective view of future directions in factor analysis and related methods. In so doing, it demonstrates how and why factor analysis is considered to be one of the methodological pillars of behavioral research. Featuring an outstanding collection of contributors, this volume offers unique insights on factor analysis and its related methods. Several chapters have a clear historical perspective, while others present new ideas along with historical summaries. In addition, the book reviews some of the extensions of factor analysis to such techniques as latent growth curve models, models for categorical data, and structural equation models. Factor Analysis at 100 will appeal to graduate students and researchers in the behavioral, social, health, and biological sciences who use this technique in their research. A basic knowledge of factor analysis is required and a working knowledge of linear algebra is helpful.


Large Dimensional Factor Analysis

Large Dimensional Factor Analysis
Author: Jushan Bai
Publisher: Now Publishers Inc
Total Pages: 90
Release: 2008
Genre: Business & Economics
ISBN: 1601981449

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Large Dimensional Factor Analysis provides a survey of the main theoretical results for large dimensional factor models, emphasizing results that have implications for empirical work. The authors focus on the development of the static factor models and on the use of estimated factors in subsequent estimation and inference. Large Dimensional Factor Analysis discusses how to determine the number of factors, how to conduct inference when estimated factors are used in regressions, how to assess the adequacy pf observed variables as proxies for latent factors, how to exploit the estimated factors to test unit root tests and common trends, and how to estimate panel cointegration models.


Foundations of factor analysis

Foundations of factor analysis
Author: John Lawrence Stover
Publisher:
Total Pages: 130
Release: 1975
Genre: Factor analysis
ISBN:

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A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio

A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio
Author: Marley Watkins
Publisher: Routledge
Total Pages: 199
Release: 2020-12-29
Genre: Psychology
ISBN: 1000336565

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This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of R and RStudio code, and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.