結(jié)構(gòu)方程模型

內(nèi)容概要

　　《應用統(tǒng)計學叢書·結(jié)構(gòu)方程模型：Mplus與應用（英文版）》以通俗易懂的方式系統(tǒng)地闡述結(jié)構(gòu)方程模型的基本概念和統(tǒng)計原理，側(cè)重各種結(jié)構(gòu)方程模型的實際應用?！稇媒y(tǒng)計學叢書·結(jié)構(gòu)方程模型：Mplus與應用（英文版）》采用國際著名SEM軟件Mplus，使用真實數(shù)據(jù)來演示各種常見的以及某些新近發(fā)展起來的較高級的結(jié)構(gòu)方程模型，提供相應的Mplus程序，并詳細解讀程序輸出結(jié)果。參照《應用統(tǒng)計學叢書·結(jié)構(gòu)方程模型：Mplus與應用（英文版）》提供的例題和相應的計算機程序，讀者便能自己實踐各種SEM模型。本書可作為大學社會科學及公共衛(wèi)生學院研究生以及統(tǒng)計和生物統(tǒng)計專業(yè)本科生教材，也可作為相關(guān)學科的研究人員從事統(tǒng)計分析的工具書。

書籍目錄

1 Introduction
1.1 Modelformulation
1.1.1 Measurement model
1.1.2 Structuralmodel
1.1.3 Model formulation in equations
1.2 Modelidentification
1.3 Modelestimation
1.4 Modelevaluation
1.5 Modelmodification
1.6 Computer programs for SEM
Appendix 1.A Expressing variances and covariances among observed
variables as functions of model parameters
Appendix 1.B Maximum likelihood function for SEM
2 Confirmatory factor analysis
2.1 Basics ofCFA model
2.2 CFA model with continuous indicators
2.3 CFA model with non-normal and censoredcontinuous
indicators
2.3.1 Testingnon-normality
2.3.2 CFA model with non-normalindicators
2.3.3 CFA model with censored data
2.4 CFA model with categoricalindicators
2.4.1 CFAmodelwithbinaryindicators '
2.4.2 CFA model with ordered categoricalindicators
2.5 Higher order CFA model
Appendix 2.A BSI-18 instrument
Appendix 2.B Item reliability
Appendix 2.C Cronbach's alpha coefficient
Appendix 2.D Calculating probabilities using PROBIT regression
Coefficients
3 Structuralequations withlatent variables
3.1 MIMIC model
3.2 Structuralequationmodel
3.3 Correcting for measurement errorsin single indicator
variables
3.4 Testinginteractionsinvolvinglatentvariables
Appendix 3.A Influence of measurement errors
4 Latent growth models for longitudinal data analysis
4.1 LinearLGM
4.2 NonlinearLGM
4.3 Multi-processLGM
4.4 Two-partLGM
4.5 LGM with categoricaloutcomes
5 Multi-groupmodeling
5.1 Multi-group CFA model
5.1.1 Multi-group first-order CFA
5.1.2 Multi-group second-order CFA
5.2 Multi-group SEM model
5.3 Multi-groupLGM
6 Mixturemodeling
6.1 LCAmodel
6.1.1 ExampleofLCA
6.1.2 Example of LCA model with covariates
6.2 LTAmodel
6.2.1 ExampleofLTA
6.3 Growth mixture model
6.3.1 Example of GMM
6.4 Factor mixture model
Appendix 6.A Including covariate in the LTA model
7 Sample size for structural equation modeling
7.1 The rules of thumb for sample size needed for SEM
7.2 Satorra and Saris's method for sample size estimation
7.2.1 Application of Satorra and Saris's method to CFA model
7.2.2 Application of Satorra and Saris's method to LGM
7.3 Monte Carlo simulation for sample size estimation
7.3.1 Application ofMonte Carlo simulation to CFA model
7.3.2 Application of Monte Carlo simulation to LGM
……
References
Index

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