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Foundations Of Factor Analysis
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Book Synopsis Foundations of Factor Analysis by : Stanley A Mulaik
Download or read book Foundations of Factor Analysis written by Stanley A Mulaik and published by CRC Press. This book was released on 2009-09-25 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Confirmatory Factor Analysis by : J. Micah Roos
Download or read book Confirmatory Factor Analysis written by J. Micah Roos and published by SAGE Publications. This book was released on 2021-10-19 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measurement connects theoretical concepts to what is observable in the empirical world, and is fundamental to all social and behavioral research. In this volume, J. Micah Roos and Shawn Bauldry introduce a popular approach to measurement: Confirmatory Factor Analysis (CFA). As the authors explain, CFA is a theoretically informed statistical framework for linking multiple observed variables to latent variables that are not directly measurable. The authors begin by defining terms, introducing notation, and illustrating a wide variety of measurement models with different relationships between latent and observed variables. They proceed to a thorough treatment of model estimation, followed by a discussion of model fit. Most of the volume focuses on measures that approximate continuous variables, but the authors also devote a chapter to categorical indicators. Each chapter develops a different example (sometimes two) covering topics as diverse as racist attitudes, theological conservatism, leadership qualities, psychological distress, self-efficacy, beliefs about democracy, and Christian nationalism drawn mainly from national surveys. Data to replicate the examples are available on a companion website, along with code for R, Stata, and Mplus.
Book Synopsis Confirmatory Factor Analysis for Applied Research, Second Edition by : Timothy A. Brown
Download or read book Confirmatory Factor Analysis for Applied Research, Second Edition written by Timothy A. Brown and published by Guilford Publications. This book was released on 2015-01-07 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 ...
Book Synopsis Exploratory Factor Analysis by : W. Holmes Finch
Download or read book Exploratory Factor Analysis written by W. Holmes Finch and published by SAGE Publications. This book was released on 2019-09-05 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis The Wiley Handbook of Psychometric Testing by : Paul Irwing
Download or read book The Wiley Handbook of Psychometric Testing written by Paul Irwing and published by John Wiley & Sons. This book was released on 2018-02-12 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: A must-have resource for researchers, practitioners, and advanced students interested or involved in psychometric testing Over the past hundred years, psychometric testing has proved to be a valuable tool for measuring personality, mental ability, attitudes, and much more. The word ‘psychometrics’ can be translated as ‘mental measurement’; however, the implication that psychometrics as a field is confined to psychology is highly misleading. Scientists and practitioners from virtually every conceivable discipline now use and analyze data collected from questionnaires, scales, and tests developed from psychometric principles, and the field is vibrant with new and useful methods and approaches. This handbook brings together contributions from leading psychometricians in a diverse array of fields around the globe. Each provides accessible and practical information about their specialist area in a three-step format covering historical and standard approaches, innovative issues and techniques, and practical guidance on how to apply the methods discussed. Throughout, real-world examples help to illustrate and clarify key aspects of the topics covered. The aim is to fill a gap for information about psychometric testing that is neither too basic nor too technical and specialized, and will enable researchers, practitioners, and graduate students to expand their knowledge and skills in the area. Provides comprehensive coverage of the field of psychometric testing, from designing a test through writing items to constructing and evaluating scales Takes a practical approach, addressing real issues faced by practitioners and researchers Provides basic and accessible mathematical and statistical foundations of all psychometric techniques discussed Provides example software code to help readers implement the analyses discussed
Book Synopsis Factor Analysis at 100 by : Robert Cudeck
Download or read book Factor Analysis at 100 written by Robert Cudeck and published by Routledge. This book was released on 2007-03-06 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Making Sense of Factor Analysis by : Marjorie A. Pett
Download or read book Making Sense of Factor Analysis written by Marjorie A. Pett and published by SAGE. This book was released on 2003-03-21 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Introduction to Factor Analysis by : Jae-On Kim
Download or read book Introduction to Factor Analysis written by Jae-On Kim and published by SAGE. This book was released on 1978-11 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Modern Factor Analysis by : Harry Horace Harman
Download or read book Modern Factor Analysis written by Harry Horace Harman and published by . This book was released on 2003-01-01 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio by : Marley W. Watkins
Download or read book A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio written by Marley W. Watkins and published by Routledge. This book was released on 2020-12-30 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling by : Larry Hatcher
Download or read book A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling written by Larry Hatcher and published by SAS Institute. This book was released on 2013-03-01 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Exploratory Factor Analysis by : Leandre R. Fabrigar
Download or read book Exploratory Factor Analysis written by Leandre R. Fabrigar and published by Oxford University Press. This book was released on 2012-01-12 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Scientific Foundations of Clinical Assessment by : Stephen N. Haynes
Download or read book Scientific Foundations of Clinical Assessment written by Stephen N. Haynes and published by Taylor & Francis. This book was released on 2011-03-07 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific Foundations of Clinical Assessment is a user-friendly overview of the most important principles and concepts of clinical assessment. It provides readers with a science-based framework for interpreting assessment research and making good assessment decisions, such as selecting the best instruments and measures and interpreting the obtained assessment data. Written in a direct and highly readable fashion, with plenty of clinical examples that illustrate the relevance of psychometric principles and assessment research, this text is one every professional and graduate student needs to read. Numerous elements are used consistently throughout the book to facilitate understanding and retention, such as: • text boxes that provide extended presentations of the application of principles and research • end-of-chapter summaries that review key issues covered, and • additional recommended sources for each chapter. A detailed glossary that defines key measurement and assessment concepts is also included, making this book an invaluable reference and supplementary text for anyone who does clinical assessment in the health and mental health domains.
Book Synopsis Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators by : Tailen Hsing
Download or read book Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators written by Tailen Hsing and published by John Wiley & Sons. This book was released on 2015-05-06 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA). The self–contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self–adjoint and non self–adjoint operators. The probabilistic foundation for FDA is described from the perspective of random elements in Hilbert spaces as well as from the viewpoint of continuous time stochastic processes. Nonparametric estimation approaches including kernel and regularized smoothing are also introduced. These tools are then used to investigate the properties of estimators for the mean element, covariance operators, principal components, regression function and canonical correlations. A general treatment of canonical correlations in Hilbert spaces naturally leads to FDA formulations of factor analysis, regression, MANOVA and discriminant analysis. This book will provide a valuable reference for statisticians and other researchers interested in developing or understanding the mathematical aspects of FDA. It is also suitable for a graduate level special topics course.
Book Synopsis Large Dimensional Factor Analysis by : Jushan Bai
Download or read book Large Dimensional Factor Analysis written by Jushan Bai and published by Now Publishers Inc. This book was released on 2008 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Structural Equation Modeling by : David Kaplan
Download or read book Structural Equation Modeling written by David Kaplan and published by SAGE Publications. This book was released on 2008-07-23 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using detailed, empirical examples, Structural Equation Modeling, Second Edition, presents a thorough and sophisticated treatment of the foundations of structural equation modeling (SEM). It also demonstrates how SEM can provide a unique lens on the problems social and behavioral scientists face. Intended Audience While the book assumes some knowledge and background in statistics, it guides readers through the foundations and critical assumptions of SEM in an easy-to-understand manner.
Book Synopsis Statistical Foundations of Data Science by : Jianqing Fan
Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
