Exploratory Factor Analysis with SAS
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: http://support.sas.com/publishing/import_ue.data.html
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Exploratory Factor Analysis with SAS
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: http://support.sas.com/publishing/import_ue.data.html
15.49 In Stock
Exploratory Factor Analysis with SAS

Exploratory Factor Analysis with SAS

by Jason W. Osborne, Isaac P Cook
Exploratory Factor Analysis with SAS

Exploratory Factor Analysis with SAS

by Jason W. Osborne, Isaac P Cook

eBook

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Overview

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: http://support.sas.com/publishing/import_ue.data.html

Product Details

ISBN-13: 9781629602417
Publisher: SAS Institute
Publication date: 03/28/2016
Sold by: Barnes & Noble
Format: eBook
Pages: 232
File size: 3 MB

About the Author

Jason W. Osborne, PhD, is an Educational Psychologist and Statistician and is currently Dean of the Graduate School at Clemson University. He is the author of several books and over 70 peer-reviewed articles; he is an Accredited Professional Statistician (American Statistical Association), and his work has been cited over 8,000 times. His passion is dissemination of best practices in statistics and research methods. He is a 3rd degree black belt in Songahm Taekwondo, the father of three, and the rest, as Anne McCaffrey often said, changes without notice.
Erin S. Banjanovic is a Research Scientist at the Human Resources Research Organization (HumRRO), a nonprofit research organization. She works in the Validity Investigations for Education and the Workplace (VIEW) group and specializes in educational evaluation and measurement. She thoroughly enjoys using research, statistics, and programming to address real-world problems. She has served as a lead psychometric analyst on several state and national-level projects for state departments of education and national assessment consortia. She has also assisted with state-wide program evaluations and served as a database manager for a number of multisource databases. She holds a BS in human development, an MA in educational psychology, and she is currently working on her PhD in educational psychology, measurement, and evaluation.
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