本书以通俗易懂的方式系统地阐述结构方程模型的基本概念和统计原理，侧重各种结构方程模型的实际运用。本书采用国际著名SEM软件Mplus，使用真实数据来演示各种常见的以及某些新近发展起来的较高级的结构方程模型，提供相应的Mplus程序, 并详细解读程序输出结果。参照本书提供的例题和相应的计算机程序，读者便能自己实践各种SEM模型。 本书可作为大学社会科学及公共卫生学院研究生，以及统计和生物统计专业本科生教材，也可作相关学科的研究人员从事统计分析的工具书。

前辅文
第一章 绪论
  1.1 模型表述
   1.1.1 测量模型
   1.1.2 结构模型
   1.1.3 模型表达方程
  1.2 模型识别
  1.3 模型估计
  1.4 模型评估
  1.5 模型修正
  附录1.1 将总体方差/协方差表达为模型参数的函数
  附录1.2 结构方程模型的最大似然函数
第二章 验证性因子分析模型
  2.1 验证性因子分析模型基础知识
  2.2 连续观察标识的验证性因子分析模型
  2.3 非正态与删截连续观察标识的验证性因子分析模型
   2.3.1 非正态性检验
   2.3.2 非正态数据的验证性因子分析模型
   2.3.3 删截标识的验证性因子分析模型
  2.4 分类观察标识的验证性因子分析模型
  2.5 高阶验证性因子分析模型
  附录2.1 BSI-18 量表
  附录2.2 条目可靠度
  附录2.3 Cronbach alpha系数
  附录2.4 分类结局测量的连接函数和概率计算
第三章 结构方程模型
  3.1 MIMIC 模型
  3.2 结构方程模型
  3.3 单标识变量中测量误差的校正
  3.4 检验涉及潜变量的交互作用
  附录3.1 测量误差的影响
第四章 潜发展模型
  4.1 线性潜发展模型
  4.2 非线性潜发展模型
  4.3 多结局测量发展过程的线性潜发展模型
  4.4 两部式潜发展模型
  4.5 分类结局测量的潜发展模型
第五章 多组模型
  5.1 多组验证性因子分析模型
   5.1.1 多组一阶验证性因子分析模型
   5.1.2 多组二阶验证性因子分析模型
  5.2 多组结构方程模型
  5.3 多组潜发展模型
第六章 结构方程建模的样本量估计
  6.1 结构方程模型样本量估计的经验法则
  6.2 Satorra-Saris 法估计样本量
   6.2.1 应用Satorra-Saris 法估计CFA 模型的样本量
   6.2.2 应用Satorra-Saris 法估计LGM 模型的样本量
  6.3 蒙特卡罗模拟法估计样本量
   6.3.1 蒙特卡罗模拟法估计CFA 模型的样本量
   6.3.2 蒙特卡罗模拟法估计LGM 模型的样本量
   6.3.3 蒙特卡罗模拟法估计具有协变量的LGM 模型样本量
   6.3.4 蒙特卡罗模拟法估计具有协变量和缺失值的fracLGM模型样本量
  6.4 基于模型拟合统计量指标的SEM 样本量估计
参考文献

王济川 1947年出生。1982年四川大学经济系毕业。1986年获美国康乃尔大学社会学硕士学位，1990年获该校社会学博士学位。1989年9月至1990年8月于美国密西根大学人口中心作博士后研究。1991年9月任职美国俄亥俄州怀特州立大学医学院社区卫生系，2000年7月至今任该系教授。2002年被聘为山东大学客座教授，2006年被聘为山东大学流行病与卫生统计学专业博士研究生兼职导师。王济川博士的主要研究领域为社会科学定量分析方法、人口分析方法及公共卫生和疾病预防研究。 

应用统计学丛书

摘自美国亚马逊读者评论

Only book that has discussed variables other than continuous!

By Mash on July 6, 2014

The only book on Mplus, which has touched on different variables than just continuous. In the real world it is necessary so for me this was a breath of fresh air. The author has done a good job in explaining concepts I have not found elsewhere. The only drawback is that formative models are not covered and the emphasis is on reflective models. Will look forward to an update, which discusses more details including formative models and how to interpret them.



Overall, an excellent source for those who wish to learn how to use SEM beyond linear SEM.

Mplus is a wonderful program, but unfortunately it is difficult to use ...

By Alberto F. Cabrera on July 6, 2015

This book provides an invaluable introduction to using Mplus for estimating latent class analyses. Mplus is a wonderful program, but unfortunately it is difficult to use if one were to rely solely on its manual. In contrast, Jichuan Wang and Xiaoqian Wang provide excellent examples as to how to unlock the potential of this incredible statistical program, while sharing with the reader some important tips for using Mplus for mixture modeling.

I recommend the book warmly

By Dr. Gabriel Liberman on September 15, 2013

I have just finished reading "Structural Equation Modeling" by Wang and Wang. I find the book extremely contributing to my knowledge of SEM. As a person who works with SEM for years and supports many studies and researches, this book advances my knowledge and allows me to get much deeper into complex SEM and puts me in the most advance modeling techniques. First, the book provides clear introduction on the mathematics and the algebra of SEM with helpful examples of graphical illustrations and the matrix algebra that generates these models. This is, of course, not the focus of the book, but only stands at the back of modeling examples. Then, the authors explain how to use different measurements for goodness of fit and quality of the model. They also discuss events when these measurements exceed the expected range and how to treat such cases. I am using the Mplus examples and they save time usually necessary for experimenting with the program before building the final model. Beyond these advantages, my experience with directly asking the authors more complex questions on topics which do not appear in the book, receives immediate clear answers. I recommend the book warmly for those who'd like to get into SEM and those who already into SEM, but would like to go further with this statistical technique.

 

Excellent book on SEM using Mplus, the best I have seen!!

By Seungyoung Hwang on July 7, 2015

I decided to buy this book because this is the only book that covers a MIMIC model (Chapter 3.1) and latent transition analysis with a covariate and interaction with latent status at time 1 with two different parameterization approaches (Appendix 6.A).



Highly recommended for those starting out in SEM using Mplus as well as refreshers who need advanced techniques along with theoretical foundations.

GREAT

By John R. Turner on April 10, 2014

This book is an excellent guide to be used in conjunction with with the Mplus user guide. The descriptions about CFA, SEM in this book are as good as any that I have read in other books on CFA and SEM. Good set of examples are provided and a fair overview of interpreting each output is also provided. This would be a great graduate course book for those using Mplus.

This is a very good applied book on structural equation modelling using Mplus

By MM on May 3, 2015

This is a very good applied book on structural equation modelling using Mplus. The book illustrates many basic as well as advanced SEM applications. The authors explain these applications in a very clear manner and provide all the necessary Mplus codes and output. I would certainly recommend the book to students/scholars wanting to use Mplus for structural equation modelling.

I would like to highly recommend this book.

By glb on January 8, 2014

I read this book last semester. It was so good that I decided to use it in my graduate applied SEM course this spring semester. The many applied examples from the social and behavioral sciences and the integration of the MPlus code into the book are also strengths of this book. Many of the graduate students in the class will need to use SEM procedures for their dissertation research and this book will be most helpful in this regard as well. I would like to highly recommend this book.

Excellent Book

By Eric Kim on June 6, 2013

I'm a grad student and I've taken one SEM course (which was taught using LISREL). I also read Kline's SEM book (which is excellent).



I found this book to be easy to read. All the concepts were explained clearly. The authors went through several examples and provided the syntax, output, and described the output quite well. I would highly recommend this book for people trying to figure out how to implement their knowledge of SEM in Mplus. If you are new to SEM, I would suggest taking a class or reading Kline first, then reading this book.