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应用统计学丛书·结构方程模型 Mplus与应用 英文版【2025|PDF|Epub|mobi|kindle电子书版本百度云盘下载】

应用统计学丛书·结构方程模型 Mplus与应用 英文版
  • 王济川，王小倩著 著
  • 出版社： 北京：高等教育出版社
  • ISBN：9787040348286
  • 出版时间：2012
  • 标注页数：453页
  • 文件大小：85MB
  • 文件页数：464页
  • 主题词：统计分析－统计程序－英文

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图书目录

1 Introduction1

1.1 Model formulation2

1.1.1 Measurement model4

1.1.2 Structural model6

1.1.3 Model formulation in equations7

1.2 Model identification11

1.3 Model estimation14

1.4 Model evaluation17

1.5 Model modification23

1.6 Computer programs for SEM24

Appendix 1.A Expressing variances and covariances among observed variables as functions of model parameters25

Appendix 1.B Maximum likelihood function for SEM27

2 Confirmatory factor analysis29

2.1 Basics of CFA model30

2.2 CFA model with continuous indicators42

2.3 CFA model with non-normal and censored continuous indicators58

2.3.1 Testing non-normality58

2.3.2 CFA model with non-normal indicators59

2.3.3 CFA model with censored data65

2.4 CFA model with categorical indicators68

2.4.1 CFA model with binary indicators69

2.4.2 CFA model with ordered categorical indicators77

2.5 Higher order CFA model78

Appendix 2.A BSI-18 instrument86

Appendix 2.B Item reliability86

Appendix 2.C Cronbach's alpha coefficient88

Appendix 2.D Calculating probabilities using PROBIT regression coefficients88

3 Structural equations with latent variables90

3.1 MIMIC model90

3.2 Structural equation model119

3.3 Correcting for measurement errors in single indicator variables130

3.4 Testing interactions involving latent variables134

Appendix 3.A Influence of measurement errors139

4 Latent growth models for longitudinal data analysis141

4.1 Linear LGM142

4.2 Nonlinear LGM157

4.3 Multi-process LGM183

4.4 Two-part LGM188

4.5 LGM with categorical outcomes196

5 Multi-group modeling207

5.1 Multi-group CFA model208

5.1.1 Multi-group first-order CFA212

5.1.2 Multi-group second-order CFA245

5.2 Multi-group SEM model268

5.3 Multi-group LGM278

6 Mixture modeling289

6.1 LCA model290

6.1.1 Example of LCA296

6.1.2 Example of LCA model with covariates309

6.2 LTA model318

6.2.1 Example of LTA320

6.3 Growth mixture model340

6.3.1 Example of GMM342

6.4 Factor mixture model365

Appendix 6.A Including covariate in the LTA model375

7 Sample size for structural equation modeling391

7.1 The rules of thumb for sample size needed for SEM391

7.2 Satorra and Saris's method for sample size estimation393

7.2.1 Application of Satorra and Saris's method to CFA model394

7.2.2 Application of Satorra and Saris's method to LGM401

7.3 Monte Carlo simulation for sample size estimation405

7.3.1 Application of Monte Carlo simulation to CFA model406

7.3.2 Application of Monte Carlo simulation to LGM412

7.3.3 Application of Monte Carlo simulation to LGM with covariate415

7.3.4 Application of Monte Carlo simulation to LGM with missing values417

7.4 Estimate sample size for SEM based on model fit indices422

7.4.1 Application of MacCallum,Browne and Sugawara's method423

7.4.2 Application of Kim's method424

References429

Index447

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