Structural Equation Modeling Using R/SAS: A Step-by-Step Approach with Real Data Analysis

— —

Ding-Geng Chen Yiu-Fai Yung

Structural Equation Modeling Using R/SAS

A Step-by-Step Approach with Real Data Analysis

Ding-Geng Chen, Yiu-Fai Yung

$194

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Chapman & Hall/CRC
21 August 2023

Psychological theory & schools of thought; Psychological methodology; Probability & statistics

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

By: Ding-Geng Chen, Yiu-Fai Yung
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 453g
ISBN: 9781032431239
ISBN 10: 1032431237
Pages: 408
Publication Date: 21 August 2023
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Ding-Geng Chen, Ph.D. Professor and Executive Director in Biostatistics College of Health Solutions Arizona State University, USA. Yiu-Fai Yung, Ph.D. Senior Manager, Advanced Analytics R & D, SAS Institute Inc.

Reviews for Structural Equation Modeling Using R/SAS: A Step-by-Step Approach with Real Data Analysis

"""In sum, this book is an essential read for practitioners and students who seek to use SEM in their research. It bridges the gap between theory and practice in a manner that is both comprehensive and understandable. The structured layout, practical examples with statistical code in R and SAS, and depth of coverage make this book a valuable asset in the field of SEM."" Lifeng Lin, University of Arizona, U.S.A, Journal of the American Statistical Association, Feburary 2024."