Making Sense Of Factor Analysis

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Making Sense of Factor Analysis

Marjorie A. Pett,Nancy R. Lackey,John J. Sullivan
Making Sense of Factor Analysis Book PDF

Author : Marjorie A. Pett,Nancy R. Lackey,John J. Sullivan
Publisher : SAGE
Page : 369 pages
File Size : 43,9 Mb
Release : 2003-03-21
Category : Mathematics
ISBN : 9780761919506

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Making Sense of Factor Analysis by Marjorie A. Pett,Nancy R. Lackey,John J. Sullivan Pdf

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.

Making Sense of Multivariate Data Analysis

John Spicer
Making Sense of Multivariate Data Analysis Book PDF

Author : John Spicer
Publisher : SAGE
Page : 256 pages
File Size : 52,8 Mb
Release : 2005
Category : Mathematics
ISBN : 1412904013

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Making Sense of Multivariate Data Analysis by John Spicer Pdf

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.

Foundations of Factor Analysis

Stanley A Mulaik
Foundations of Factor Analysis Book PDF

Author : Stanley A Mulaik
Publisher : CRC Press
Page : 550 pages
File Size : 52,6 Mb
Release : 2009-09-25
Category : Mathematics
ISBN : 9781420099812

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Foundations of Factor Analysis by Stanley A Mulaik Pdf

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

Factor Analysis and Related Methods

Roderick P. McDonald
Factor Analysis and Related Methods Book PDF

Author : Roderick P. McDonald
Publisher : Psychology Press
Page : 280 pages
File Size : 55,7 Mb
Release : 2014-01-14
Category : Psychology
ISBN : 9781317768760

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Factor Analysis and Related Methods by Roderick P. McDonald Pdf

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

Larry Hatcher,Norm O'Rourke
A Step by Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling Book PDF

Author : Larry Hatcher,Norm O'Rourke
Publisher : SAS Institute
Page : 444 pages
File Size : 55,9 Mb
Release : 2013-03-01
Category : Computers
ISBN : 9781612903873

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A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling by Larry Hatcher,Norm O'Rourke Pdf

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.

Exploratory Factor Analysis

W. Holmes Finch
Exploratory Factor Analysis Book PDF

Author : W. Holmes Finch
Publisher : SAGE Publications
Page : 133 pages
File Size : 40,5 Mb
Release : 2019-09-05
Category : Social Science
ISBN : 9781544339870

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Exploratory Factor Analysis by W. Holmes Finch Pdf

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.

Exploratory Factor Analysis

Leandre R. Fabrigar,Duane T. Wegener
Exploratory Factor Analysis Book PDF

Author : Leandre R. Fabrigar,Duane T. Wegener
Publisher : Oxford University Press
Page : 170 pages
File Size : 43,6 Mb
Release : 2012-01-12
Category : Medical
ISBN : 9780199734177

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Exploratory Factor Analysis by Leandre R. Fabrigar,Duane T. Wegener Pdf

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.

Exploratory Factor Analysis

Diana Mindrila
Exploratory Factor Analysis Book PDF

Author : Diana Mindrila
Publisher : Unknown
Page : 0 pages
File Size : 52,9 Mb
Release : 2017
Category : Exploratory factor analysis
ISBN : 1536124869

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Exploratory Factor Analysis by Diana Mindrila Pdf

In education, researchers often work with complex data sets that include a multitude of variables. One question that often arises in such contexts is whether the structure of associations that underlies the data is accounted for by a latent construct. Exploratory factor analysis is a multivariate correlational procedure that helps researchers overcome such challenges. It helps reduce large data sets into main components or identify distinct constructs that account for the pattern of correlations among observed variables. These unobservable constructs are referred to as common factors, latent variables, or internal attributes, and they exert linear influences on more than one observed variable. Although exploratory factor analysis is widely used, many applied educational researchers and practitioners are not yet familiar with this procedure and are intimidated by the technical terminology. This book provides a conceptual description of this method and includes a collection of applied research studies that illustrates the application of exploratory factor analysis in school improvement research. The first chapter provides a theoretical overview of exploratory factor analysis. It explains the purposes for which this procedure can be used, the related terminology, the distinction between key concepts, the steps that must be taken, and the criteria for making the decisions. This information can serve as a starting point for researchers who need a brief, conceptual introduction to this topic. The following chapters present a series of research studies in which exploratory factor analysis was employed either by itself or in conjunction with other statistical procedures. The studies presented in this book address a variety of research problems in the field of school improvement. They specify how the factor analytic procedure was applied, and explain the theoretical contributions and the practical applications of the factor analytic results. In most studies, results from factor analysis were used for subsequent statistical procedures, thus helping researchers address more complex research questions and enriching the results.

Best Practices in Exploratory Factor Analysis

Jason W. Osborne
Best Practices in Exploratory Factor Analysis Book PDF

Author : Jason W. Osborne
Publisher : Createspace Independent Publishing Platform
Page : 0 pages
File Size : 48,5 Mb
Release : 2014-07-23
Category : Factor analysis
ISBN : 1500594342

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Best Practices in Exploratory Factor Analysis by Jason W. Osborne Pdf

Best Practices in Exploratory Factor Analysis (EFA) is a practitioner-oriented look at this popular and often-misunderstood statistical technique. We avoid formulas and matrix algebra, instead focusing on evidence-based best practices so you can focus on getting the most from your data.Each chapter reviews important concepts, uses real-world data to provide authentic examples of analyses, and provides guidance for interpreting the results of these analysis. Not only does this book clarify often-confusing issues like various extraction techniques, what rotation is really rotating, and how to use parallel analysis and MAP criteria to decide how many factors you have, but it also introduces replication statistics and bootstrap analysis so that you can better understand how precisely your data are helping you estimate population parameters. Bootstrap analysis also informs readers of your work as to the likelihood of replication, which can give you more credibility. At the end of each chapter, the author has recommendations as to how to enhance your mastery of the material, including access to the data sets used in the chapter through his web site. Other resources include syntax and macros for easily incorporating these progressive aspects of exploratory factor analysis into your practice. The web site will also include enrichment activities, answer keys to select exercises, and other resources. The fourth "best practices" book by the author, Best Practices in Exploratory Factor Analysis continues the tradition of clearly-written, accessible guides for those just learning quantitative methods or for those who have been researching for decades.NEW in August 2014! Chapters on factor scores, higher-order factor analysis, and reliability. Chapters: 1 INTRODUCTION TO EXPLORATORY FACTOR ANALYSIS 2 EXTRACTION AND ROTATION 3 SAMPLE SIZE MATTERS 4 REPLICATION STATISTICS IN EFA 5 BOOTSTRAP APPLICATIONS IN EFA 6 DATA CLEANING AND EFA 7 ARE FACTOR SCORES A GOOD IDEA? 8 HIGHER ORDER FACTORS 9 AFTER THE EFA: INTERNAL CONSISTENCY 10 SUMMARY AND CONCLUSIONS

Introduction to Factor Analysis

Jae-On Kim,Charles W. Mueller
Introduction to Factor Analysis Book PDF

Author : Jae-On Kim,Charles W. Mueller
Publisher : SAGE
Page : 84 pages
File Size : 55,7 Mb
Release : 1978-11
Category : Mathematics
ISBN : 0803911653

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Introduction to Factor Analysis by Jae-On Kim,Charles W. Mueller Pdf

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.

Learning Statistics with R

Daniel Navarro
Learning Statistics with R Book PDF

Author : Daniel Navarro
Publisher : Lulu.com
Page : 617 pages
File Size : 43,5 Mb
Release : 2013-01-13
Category : Computers
ISBN : 9781326189723

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Learning Statistics with R by Daniel Navarro Pdf

"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Assessing Measurement Invariance for Applied Research

Craig S. Wells
Assessing Measurement Invariance for Applied Research Book PDF

Author : Craig S. Wells
Publisher : Cambridge University Press
Page : 417 pages
File Size : 47,6 Mb
Release : 2021-06-03
Category : Education
ISBN : 9781108485227

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Assessing Measurement Invariance for Applied Research by Craig S. Wells Pdf

This user-friendly guide illustrates how to assess measurement invariance using computer programs, statistical methods, and real data.

Doing Meta-Analysis with R

Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert
Doing Meta Analysis with R Book PDF

Author : Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert
Publisher : CRC Press
Page : 500 pages
File Size : 46,7 Mb
Release : 2021-09-15
Category : Mathematics
ISBN : 9781000435634

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Doing Meta-Analysis with R by Mathias Harrer,Pim Cuijpers,Toshi A. Furukawa,David D. Ebert Pdf

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book

Confirmatory Factor Analysis for Applied Research, Second Edition

Timothy A. Brown
Confirmatory Factor Analysis for Applied Research Second Edition Book PDF

Author : Timothy A. Brown
Publisher : Guilford Publications
Page : 482 pages
File Size : 52,9 Mb
Release : 2015-01-07
Category : Science
ISBN : 9781462517794

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Confirmatory Factor Analysis for Applied Research, Second Edition by Timothy A. Brown Pdf

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 ...

Best Practices in Quantitative Methods

Jason W. Osborne
Best Practices in Quantitative Methods Book PDF

Author : Jason W. Osborne
Publisher : SAGE
Page : 609 pages
File Size : 53,8 Mb
Release : 2008
Category : Social Science
ISBN : 9781412940658

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Best Practices in Quantitative Methods by Jason W. Osborne Pdf

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.