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A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, Second Edition

A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, Second Edition
Author: Ph. D. Norm O'Rourke
Publisher: SAS Institute
Total Pages: 444
Release: 2013-03-23
Genre: Computers
ISBN: 9781642952919

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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.


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

A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling
Author: Larry Hatcher
Publisher: SAS Institute
Total Pages: 444
Release: 2013-03-01
Genre: Computers
ISBN: 1612903878

Download A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling Book in PDF, ePub and Kindle

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.


A Step-by-Step Approach to Using SAS for Univariate & Multivariate Statistics

A Step-by-Step Approach to Using SAS for Univariate & Multivariate Statistics
Author: Norm O'Rourke
Publisher: SAS Institute
Total Pages: 552
Release: 2005
Genre: Computers
ISBN: 1590474171

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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.


A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, Second Edition

A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, Second Edition
Author: Norm O'Rourke, Ph.D., R.Psych.
Publisher: SAS Institute
Total Pages: 444
Release: 2013-03-23
Genre: Computers
ISBN: 1629592447

Download A Step-by-Step Approach to Using SAS for Factor Analysis and Structural Equation Modeling, Second Edition Book in PDF, ePub and Kindle

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.


Structural Equation Modeling Using R/SAS

Structural Equation Modeling Using R/SAS
Author: Ding-Geng Chen
Publisher: CRC Press
Total Pages: 429
Release: 2023-08-21
Genre: Mathematics
ISBN: 1000920887

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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


A Beginner's Guide to Structural Equation Modeling

A Beginner's Guide to Structural Equation Modeling
Author: Randall E. Schumacker
Publisher: Psychology Press
Total Pages: 590
Release: 2004-06-24
Genre: Psychology
ISBN: 1135641919

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The second edition features: a CD with all of the book's Amos, EQS, and LISREL programs and data sets; new chapters on importing data issues related to data editing and on how to report research; an updated introduction to matrix notation and programs that illustrate how to compute these calculations; many more computer program examples and chapter exercises; and increased coverage of factors that affect correlation, the 4-step approach to SEM and hypothesis testing, significance, power, and sample size issues. The new edition's expanded use of applications make this book ideal for advanced students and researchers in psychology, education, business, health care, political science, sociology, and biology. A basic understanding of correlation is assumed and an understanding of the matrices used in SEM models is encouraged.


Confirmatory Factor Analysis for Applied Research, Second Edition

Confirmatory Factor Analysis for Applied Research, Second Edition
Author: Timothy A. Brown
Publisher: Guilford Publications
Total Pages: 482
Release: 2015-01-07
Genre: Science
ISBN: 146251779X

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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 ...


Growth Modeling

Growth Modeling
Author: Kevin J. Grimm
Publisher: Guilford Publications
Total Pages: 558
Release: 2016-10-17
Genre: Social Science
ISBN: 1462526063

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Growth models are among the core methods for analyzing how and when people change. Discussing both structural equation and multilevel modeling approaches, this book leads readers step by step through applying each model to longitudinal data to answer particular research questions. It demonstrates cutting-edge ways to describe linear and nonlinear change patterns, examine within-person and between-person differences in change, study change in latent variables, identify leading and lagging indicators of change, evaluate co-occurring patterns of change across multiple variables, and more. User-friendly features include real data examples, code (for Mplus or NLMIXED in SAS, and OpenMx or nlme in R), discussion of the output, and interpretation of each model's results. User-Friendly Features *Real, worked-through longitudinal data examples serving as illustrations in each chapter. *Script boxes that provide code for fitting the models to example data and facilitate application to the reader's own data. *"Important Considerations" sections offering caveats, warnings, and recommendations for the use of specific models. *Companion website supplying datasets and syntax for the book's examples, along with additional code in SAS/R for linear mixed-effects modeling.


Analysis of Observational Health Care Data Using SAS

Analysis of Observational Health Care Data Using SAS
Author: Douglas E. Faries
Publisher: SAS Press
Total Pages: 0
Release: 2010
Genre: Medical care
ISBN: 9781607642275

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This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.