A Step-by-step Approach to Using the SAS System for Factor Analysis and Structural Equation Modeling PDF Download

Author: Larry Hatcher
Publisher: SAS Press
ISBN:
Category : Computers
Languages : en
Pages : 612

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Book Description
Packed with concrete examples, Larry Hatcher's Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling provides an introduction to more advanced statistical procedures and includes handy appendixes that give basic instruction in using SAS. Novice SAS users will find all they need in this one volume to master SAS basics and to move into advanced statistical analyses. Featured is a simple, step-by-step approach to testing structural equation models with latent variables using the CALIS procedure. The following topics are explained in easy-to-understand terms: exploratory factor analysis, principal component analysis, and developing measurement models with confirmatory factor analysis. Other topics of note include "LISREL-type" analyses with the user-friendly PROC CALIS and solving problems encountered in real-world social science research.

Author: Larry Hatcher
Publisher: SAS Institute
ISBN: 1612903878
Category : Computers
Languages : en
Pages : 444

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Book Description
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.

Author: Ph. D. Norm O'Rourke
Publisher: SAS Institute
ISBN: 9781642952919
Category : Computers
Languages : en
Pages : 444

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Book Description
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 users, even 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.

Author: Norm O'Rourke
Publisher: SAS Institute
ISBN: 1590474171
Category : Computers
Languages : en
Pages : 552

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Book Description
Providing practice data inspired by actual studies, this book explains how to choose the right statistic, understand the assumptions underlying the procedure, prepare an SAS program for an analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association.

Author: R. O'Rourke
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
This easy-to-understand guide makes SEM accessible to all users. 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.

Author: Ph. D. Norm O'Rourke
Publisher: SAS Institute
ISBN: 9781642952926
Category : Computers
Languages : en
Pages : 548

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Book Description
Updated for SAS 9, A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics, Second Edition, is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics. Clear explanations and simple language guide you through the research terminology, data input, data manipulation, and types of statistical analysis that are most commonly used in the social and behavioral sciences. Providing practice data inspired by actual studies, this book teaches you how to choose the right statistic, understand the assumptions underlying the procedure, prepare the SAS program for the analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association. Step by step, authors Norm O'Rourke, Larry Hatcher, and Edward Stepanski demonstrate how to perform the following types of analysis: simple descriptive statistics, measures of bivariate association, t tests for independent samples and paired samples, ANOVA and MANOVA, multiple regression, principal component analysis, and assessing scale reliability with coefficient alpha. This text is ideally suited to students who are beginning their study of data analysis, and to professors and researchers who want a handy reference on their bookshelf.

Author: Edward J. Stepanski
Publisher:
ISBN: 9781590477779
Category : Mathematical statistics
Languages : en
Pages : 514

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Book Description
Updated for SAS9, this second edition is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics. Clear explanations and simple language guide you through the research terminology, data input, data manipulation, and types of statistical analysis that are most commonly used in the social and behavioral sciences. Providing practice data inspired by actual studies, this book teaches you how to choose the right statistic, understand the assumptions underlying the procedure, prepare the SAS program for the analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association. Step by step you will learn how to perform the following types of analysis: simple descriptive statistics, measures of bivariate association, t tests: independent samples and paired samples, NOVA and MANOVA, multiple regression, principal component analysis, and assessing scale reliability with coefficient alpha. This text is ideally suited to students who are beginning their study of data analysis, and to professors and researchers who want a handy reference on their bookshelf.

Author: Larry Hatcher
Publisher: Books by Users Press
ISBN: 9781555446345
Category : Mathamatical statistics
Languages : en
Pages : 0

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Book Description
Researchers and students of the Social Sciences will find this book a user-friendly introduction to both the SAS System and elementary statistical procedures. Its clear presentation of more advanced statistical procedures makes it an invaluable reference guide for more experienced researchers as well. Step by step, this book guides you through the basic concepts of research and data analysis, to data input, and on to ANOVA and MANOVA. Book jacket.

Author: Norm O'Rourke
Publisher: Wiley-Interscience
ISBN: 9780470388006
Category : Mathematics
Languages : en
Pages : 0

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Book Description
This set contains: 9780471469445 A Step-by-Step Approach to Using SAS for Univariate & Multivariate Statistics, Second Edition by Norm O'Rourke, Larry Hatcher, Edward J. Stepanski, SAS Institute Inc and 9780471226185 An Introduction to Categorical Data Analysis, Second Edition by Alan Agresti.

Author: Ding-Geng Chen
Publisher: CRC Press
ISBN: 1000920887
Category : Mathematics
Languages : en
Pages : 429

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Book Description
There has been considerable attention to making the methodologies of structural equation modeling available to researchers, practitioners, and students along with commonly used software. Structural Equation Modelling Using R/SAS aims to bring it all together to provide a concise point-of-reference for the most commonly used structural equation modeling from the fundamental level to the advanced level. This book is intended to contribute to the rapid development in structural equation modeling and its applications to real-world data. Straightforward explanations of the statistical theory and models related to structural equation models are provided, using a compilation of a variety of publicly available data, to provide an illustration of data analytics in a step-by-step fashion using commonly used statistical software of R and SAS. This book is appropriate for anyone who is interested in learning and practicing structural equation modeling, especially in using R and SAS. It is useful for applied statisticians, data scientists and practitioners, applied statistical analysts and scientists in public health, and academic researchers and graduate students in statistics, whilst also being of use to R&D professionals/practitioners in industry and governmental agencies. Key Features: Extensive compilation of commonly used structural equation models and methods from fundamental to advanced levels Straightforward explanations of the theory related to the structural equation models Compilation of a variety of publicly available data Step-by-step illustrations of data analysis using commonly used statistical software R and SAS Data and computer programs are available for readers to replicate and implement the new methods to better understand the book contents and for future applications Handbook for applied statisticians and practitioners