本研究着重考察大数据时代应用语言学中的结构方程建模。基本思路是：通过语料库技术，将大数据转化成小数据（结构化数据），然后利用结构方程技术处理结构化数据，建立模型，探索规律，指导大数据处理、教学与研究。

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Contents
Chapter 1 Introduction 1
1.1 Applied Linguistics and SEM in Applied Linguistics 1
1.2 Big Data Corpora and the Extraction of Small Data 4
1.3 Amos and Its Uses in SEM 25
1.4 Summary 38
Chapter 2 Parameter Estimation and Test 39
2.1 Estimation of Parameters 39
2.2 Test of Parameters 46
2.3 Summary 51
Chapter 3 Path Models 52
3.1 Types of Elementary Path Models 52
3.2 Examples of the Analysis of Path Models 55
3.3 Summary 88
Chapter 4 Factor Analysis Models and Structural Regression Models 90
4.1 Factor Analysis Models 90
4.2 Structural Regression Models 112
4.3 Summary 127
Chapter 5 Data Imputation 129
5.1 Regression Imputation 129
5.2 Stochastic Regression Imputation 133
5.3 Bayesian Imputation 135
5.4 Multiple Imputation 137
5.5 Summary 140
Chapter 6 Analyses with Censored and Ordered-Category Data 141
6.1 Analyses with Censored Data 141
6.2 Analyses with Ordered-Category Data 148
6.3 Summary 157
Chapter 7 Bootstrapping 158
7.1 Bootstrapping Used in Model Comparison 158
7.2 Bootstrapping Used in Estimation Method Comparison 164
7.3 Summary 169
References 170