李云仙所著的《结构方程模型的选择方法研究——一种基于贝叶斯准则的模型选择方法》概括了本学科的近期发展，并有如下特点：示范如何使用强大的统计计算工具得到贝叶斯结果；讨论用于模型比较的贝叶斯因子和偏差信息准则；涵盖多种复杂的模型；通过模拟研究以及来自工商管理学、教育学、心理学、公共卫生和社会学的实际数据说明所提出的方法。

Chapter 1 Introduction

 1.1 Overview

 1.2 Lv Measure for Model Selection

 1.3 Outline of the Book

Chapter 2 Lv Measure for Nonlinear Structural Equation Models

 2.1 Introduction

 2.2 Brief Review of the Lv Measure

 2.3 Model Description

 2.4 Lv Measure for Nonlinear Structural Equation Models

 2.5 A Simulation Study

 2.6 A Real Example

 2.7 Discussion

Chapter 3 Lv Measure for Nonlinear Structural Equation Models with Mixed Continuous and Categorical Data

 3.1 Introduction

 3.2 Model Description

 3.3 Lv Measure for Nonlinear SEMs with Mixed Continuous and Ordered Categorical Data

 3.4 A Simulation Study

 3.5 A Real Example

 3.6 Discussion

Chapter 4 Lv Measure for Model Selection of Two-Level Structural Equation Models

 4.1 Introduction

 4.2 Model Description

 4.3 Lv Measure for Two-Level Structural Equation Models

 4.4 A Simulation Study

 4.5 A Real Example

 4.6 Discussion

Chapter 5 Lv Measure for Finite Mixture Structural Equation Models

 5.1 Introduction

 5.2 Model Description

 5.3 Lv Measure for Finite Mixture SEMs

 5.4 A Simulation Study

 5.5 A Real Example

 5.6 Discussion

Chapter 6 Conclusions and Further Developments

 6.1 Conclusions

 6.2 Discussion and Further Developments

Appendix A Variable Description in Real Examples

Appendix B WinBUGS and R2winBUGS

Appendix C WinBUGS and R2winBUGS Program in Chapter 3

References

Acknowledgement