A Step-by-Step Guide to Exploratory Factor Analysis with SPSS

2021-06-21

PDF A Step-by-Step Guide to Exploratory Factor Analysis with SPSS Download

Author: Marley W. Watkins
Publisher: Routledge
ISBN: 1000400271
Category : Computers
Languages : en
Pages : 210

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using SPSS. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots and code from SPSS 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 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.

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

2020-12-30

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

Author: Marley W. Watkins
Publisher: Routledge
ISBN: 1000336824
Category : Psychology
Languages : en
Pages : 227

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.

A Step-by-Step Guide to Exploratory Factor Analysis with Stata

2021-09-08

PDF A Step-by-Step Guide to Exploratory Factor Analysis with Stata Download

Author: Marley W. Watkins
Publisher: Routledge
ISBN: 1000426858
Category : Psychology
Languages : en
Pages : 210

This is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using Stata. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of Stata 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 when 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.

Exploratory Factor Analysis

2012-01-12

PDF Exploratory Factor Analysis Download

Author: Leandre R. Fabrigar
Publisher: Oxford University Press
ISBN: 0199734178
Category : Medical
Languages : en
Pages : 170

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.

Best Practices in Exploratory Factor Analysis

2014-07-23

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Author: Jason W. Osborne
Publisher: Createspace Independent Publishing Platform
ISBN: 9781500594343
Category : Factor analysis
Languages : en
Pages : 0

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

IBM SPSS Statistics 23 Step by Step

2016-03-22

PDF IBM SPSS Statistics 23 Step by Step Download

Author: Darren George
Publisher: Routledge
ISBN: 1134793405
Category : Education
Languages : en
Pages : 840

IBM SPSS Statistics 23 Step by Step: A Simple Guide and Reference, 14e, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of vivid, four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS. All datasets used in the book are available for download at: https://www.routledge.com/products/ 9780134320250

Factor Analysis and Related Methods

2014-01-14

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Author: Roderick P. McDonald
Publisher: Psychology Press
ISBN: 1317768760
Category : Psychology
Languages : en
Pages : 280

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 Concise Guide to Market Research

2014-07-29

PDF A Concise Guide to Market Research Download

Author: Marko Sarstedt
Publisher: Springer
ISBN: 3642539653
Category : Business & Economics
Languages : en
Pages : 347

This accessible, practice-oriented and compact text provides a hands-on introduction to market research. Using the market research process as a framework, it explains how to collect and describe data and presents the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis and cluster analysis. The book describes the theoretical choices a market researcher has to make with regard to each technique, discusses how these are converted into actions in IBM SPSS version 22 and how to interpret the output. Each chapter concludes with a case study that illustrates the process using real-world data. A comprehensive Web appendix includes additional analysis techniques, datasets, video files and case studies. Tags in the text allow readers to quickly access Web content with their mobile device. The new edition features: Stronger emphasis on the gathering and analysis of secondary data (e.g., internet and social networking data) New material on data description (e.g., outlier detection and missing value analysis) Improved use of educational elements such as learning objectives, keywords, self-assessment tests, case studies, and much more Streamlined and simplified coverage of the data analysis techniques with more rules-of-thumb Uses IBM SPSS version 22

Using SPSS for Windows

2006-01-27

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Author: Susan B. Gerber
Publisher: Springer Science & Business Media
ISBN: 0387276041
Category : Computers
Languages : en
Pages : 224

The second edition of this popular guide demonstrates the process of entering and analyzing data using the latest version of SPSS (12.0), and is also appropriate for those using earlier versions of SPSS. The book is easy to follow because all procedures are outlined in a step-by-step format designed for the novice user. Students are introduced to the rationale of statistical tests and detailed explanations of results are given through clearly annotated examples of SPSS output. Topics covered range from descriptive statistics through multiple regression analysis. In addition, this guide includes topics not typically covered in other books such as probability theory, interaction effects in analysis of variance, factor analysis, and scale reliability. Chapter exercises reinforce the text examples and may be performed for further practice, for homework assignments, or in computer laboratory sessions. This book can be used in two ways: as a stand-alone manual for students wishing to learn data analysis techniques using SPSS for Windows, or in research and statistics courses to be used with a basic statistics text. The book provides hands-on experience with actual data sets, helps students choose appropriate statistical tests, illustrates the meaning of results, and provides exercises to be completed for further practice or as homework assignments. Susan B. Gerber, Ph.D. is Research Assistant Professor of Education at State University of New York at Buffalo. She is director of the Educational Technology program and holds degrees in Statistics and Educational Psychology. Kristin Voelkl Finn, Ph.D. is Assistant Professor of Education at Canisius College. She teaches graduate courses in research methodology and conducts research on adolescent problem behavior.

Structural Equation Modelling Made Easy for Business and Social Science Research Using SPSS and Amos

2018-11-09

PDF Structural Equation Modelling Made Easy for Business and Social Science Research Using SPSS and Amos Download

Author: Sheena Boateng
Publisher:
ISBN: 9781730806704
Category : AMOS.
Languages : en
Pages : 216

You are welcome to Structural Equation Modelling (SEM) Made Easy for Business and Social Science Research Using SPSS and Amos. This book seeks to provide a simple practical guide to conducting quantitative data analysis. First, it presents an overview of quantitative research, by explaining different types of variables and the formulation and testing of hypotheses. Second, it presents the rubrics for designing quantitative questionnaires, explains sampling and illustrates how to determine sample size. Third, the book also explains descriptive statistics and how to conduct and present descriptive statistics in a research write-up. Fourth, it provides a step by step process to carry out exploratory factor analysis and procedures for interpreting related outputs from the statistical software package, SPSS. Fifth, it teaches how to establish reliability and validity in quantitative research. Finally, the book explains the basics of Structural Equation Modelling (SEM) and demonstrates the two-step approach to SEM analysis, the foundational concepts of measurement models, structural models, Confirmatory Factor Analysis (CFA) and Path Analysis (PA). It also teaches how to run SEM analysis using Amos, and how to interpret the resulting output. This book is essential for anyone involved in business and social science research. Its purpose is not to create a 'one best format', but to offer a practical guide in analyzing quantitative data and presenting such analysis in research papers, long essays, theses and dissertations.