傳統(tǒng)應(yīng)用語(yǔ)言學(xué)研究主要涉及結(jié)構(gòu)化數(shù)據(jù)（即小數(shù)據(jù)）。隨著信息技術(shù)發(fā)展，應(yīng)用語(yǔ)言學(xué)研究也進(jìn)入了大數(shù)據(jù)時(shí)代。這里的大數(shù)據(jù)是指應(yīng)用語(yǔ)言學(xué)研究使用的超級(jí)語(yǔ)料庫(kù)，它們具有一般大數(shù)據(jù)的基本特征。《大數(shù)據(jù)時(shí)代應(yīng)用語(yǔ)言學(xué)研究中的結(jié)構(gòu)方程建模=structural equation modeling in applied linguistics in the era of big data》屬于統(tǒng)計(jì)學(xué)和語(yǔ)料庫(kù)語(yǔ)言學(xué)交叉學(xué)科范疇，著重考察三個(gè)方面：①語(yǔ)料庫(kù)大數(shù)據(jù)的特征；②常用的語(yǔ)料庫(kù)分析軟件及其在語(yǔ)言數(shù)據(jù)提取中的應(yīng)用；③結(jié)構(gòu)方程建模的概念和原理及其利用語(yǔ)料庫(kù)數(shù)據(jù)建模的基本方法。
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
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