Making Sense of Factor Analysis

Author: Marjorie A. Pett
Publisher: SAGE
ISBN: 0761919503
Format: PDF, ePub
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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.

Statistical Factor Analysis and Related Methods

Author: Alexander T. Basilevsky
Publisher: John Wiley & Sons
ISBN: 0470317736
Format: PDF
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Statistical Factor Analysis and Related Methods Theory and Applications In bridging the gap between the mathematical and statistical theory of factor analysis, this new work represents the first unified treatment of the theory and practice of factor analysis and latent variable models. It focuses on such areas as: * The classical principal components model and sample-population inference * Several extensions and modifications of principal components, including Q and three-mode analysis and principal components in the complex domain * Maximum likelihood and weighted factor models, factor identification, factor rotation, and the estimation of factor scores * The use of factor models in conjunction with various types of data including time series, spatial data, rank orders, and nominal variable * Applications of factor models to the estimation of functional forms and to least squares of regression estimators

An Easy Guide to Factor Analysis

Author: Paul Kline
Publisher: Routledge
ISBN: 1317725603
Format: PDF
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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).

Foundations of factor analysis

Author: Stanley A. Mulaik
Publisher: Chapman & Hall/CRC
ISBN: 9781420099614
Format: PDF, ePub, Docs
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Providing a practical, thorough understanding of how factor analysis works,Foundations of Factor Analysis, Second Editiondiscusses 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 edition takes into account the various developments that have occurred since the publication of the original edition. New to the Second Edition A new chapter on the multivariate normal distribution, its general properties, and the concept of maximum-likelihood estimation More complete coverage of descriptive factor analysis and doublet factor analysis A rewritten chapter on analytic oblique rotation that focuses on the gradient projection algorithm and its applications Discussions on the developments of factor score indeterminacy A revised chapter on confirmatory factor analysis that addresses philosophy of science issues, model specification and identification, parameter estimation, and algorithm derivation Presenting the mathematics only as needed to understand the derivation of an equation or procedure, this textbook prepares students for later courses on structural equation modeling. It enables them to choose the proper factor analytic procedure, make modifications to the procedure, and produce new results.

Factor Analysis and Related Methods

Author: Roderick P. McDonald
Publisher: Psychology Press
ISBN: 1317768779
Format: PDF, ePub
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Factor Analysis is a genetic term for a somewhat vaguely delimited set of techniques for data processing, mainly applicable to the social and biological sciences. These techniques have been developed for the analysis of mutual relationships among a number of measurements made on a number of measurable entities. In the broad sense, factor analysis comprises a number of statistical models which yield testable hypotheses -- hypotheses that may confirm or disconfirm in terms of the usual statistical procedures for making tests of significance. It also comprises a number of simplifying procedures for the approximate description of data, which do not in any sense constitute disconfirmable hypotheses, except in the loose sense that they supply approximations to the data. In literature, the two types of analysis have often been confused. This book clarifies the concepts of factor analysis for students or professionals in the social sciences who wish to know the technique, rather than the mathematics, of factor theory. Mathematical concepts are described to have an intuitive meaning for the non-mathematical reader. An account of the elements of matrix algebra, in the appendix, and the (mathematical) notes following each chapter will help the reader who wishes to receive a more advanced treatment of the subject. Factor Analysis and Related Methods should prove a useful text for graduate and advanced undergraduate students in economics, the behavioral sciences, and education. Researchers and practitioners in those fields will also find this book a handy reference.

A First Course in Factor Analysis

Author: Andrew L. Comrey
Publisher: Psychology Press
ISBN: 1317844076
Format: PDF
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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.

Exploratory Factor Analysis with SAS

Author: Jason W. Osborne, PhD
Publisher: SAS Institute
ISBN: 1629602418
Format: PDF, Docs
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Explore the mysteries of Exploratory Factor Analysis (EFA) with SAS with an applied and user-friendly approach. Exploratory Factor Analysis with SAS focuses solely on EFA, presenting a thorough and modern treatise on the different options, in accessible language targeted to the practicing statistician or researcher. This book provides real-world examples using real data, guidance for implementing best practices in the context of SAS, interpretation of results for end users, and it provides resources on the book's author page. Faculty teaching with this book can utilize these resources for their classes, and individual users can learn at their own pace, reinforcing their comprehension as they go. Exploratory Factor Analysis with SAS reviews each of the major steps in EFA: data cleaning, extraction, rotation, interpretation, and replication. The last step, replication, is discussed less frequently in the context of EFA but, as we show, the results are of considerable use. Finally, two other practices that are commonly applied in EFA, estimation of factor scores and higher-order factors, are reviewed. Best practices are highlighted throughout the chapters. A rudimentary working knowledge of SAS is required but no familiarity with EFA or with the SAS routines that are related to EFA is assumed. Using SAS University Edition? You can use the code and data sets provided with this book. This helpful link will get you started:

SPSS Step by Step

Author: Cole Davis
Publisher: Policy Press
ISBN: 1447306279
Format: PDF, Kindle
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A logically ordered guide to analysing everyday problems, SPSS Step by Step is distinctive in being both easy to grasp and readable.

Factor analysis

Author: Ertel, Suitbert
Publisher: Universitätsverlag Göttingen
ISBN: 3863951336
Format: PDF, ePub, Mobi
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Exploratory factor analysis (EFA) is a statistical tool for digging out hidden factors which give rise to the diversity of manifest objectives in psychology, medicine and other sciences. EFA had its heyday as psychologist Leon Thurstone (1935 and 1948) based EFA on what he called the “principle of simple structure” (SS). This principle, however, was erroneous from the beginning what remained unrecognized despite subsequent inventions of more sophisticated statistical tools such as confirmatory analysis and structural equation modeling. These methods are highly recommended today as tolerable routes to model complexities of observation. But they did not remove the harmful errors that SS had left behind. Five chapters in this book demonstrate and explain the trouble. In chapter 2 the ailment of SS is healed by introducing an unconventional factor rotation, called Varimin. Varimin gives variables of an analysis an optimal opportunity to manifest functional interrelations underlying correlational observations. Ten applications of Varimin (in chapter 2) show that its results are superior to results obtained by the conventional Varimax procedure. Further applications are presented for sports achievements (chapter 3), intelligence (chapter 4), and personality (chapter 5). If Varimin keeps on standing the tests new theoretical building blocks will arise together with conceptual networks promoting a better understanding of the domains under study. Readers may check this prognosis by themselves using the statistical tool (Varimin) which is provided by open access in the internet.