Generalized Latent Variable Modeling

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Generalized Latent Variable Modeling[1].pdf (2.91 MB, 需要: 1 个论坛币)

2012-7-23 10:56:49 上传

Generalized Latent Variable Modeling
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Preface
Dedication
I Methodology
1 The omni-presence of latent variables
1.1 Introduction
1.2 ‘True’ variable measured with error
1.3 Hypothetical constructs
1.4 Unobserved heterogeneity
1.5 Missing values and counterfactuals
1.6 Latent responses
1.7 Generating flexible distributions
1.8 Combining information
1.9S ummary
2 Modeling different response processes
2.1 Introduction
2.2 Generalized linear models
2.3 Extensions of generalized linear models
2.4 Latent response formulation
2.5 Modeling durations or survival
2.6 Summary and further reading
3 Classical latent variable models
3.1 Introduction
3.2 Multilevel regression models
3.3 Factor models and item response models
3.4 Latent class models
3.5 Structural equation models with latent variables
3.6 Longitudinal models
3.7 Summary and further reading
4G eneral model framework
4.1 Introduction
4.2 Response model
4.3 Structural model for the latent variables
4.4 Distribution of the disturbances
4.5 Parameter restrictions and fundamental parameters
4.6 Reduced form of the latent variables and linear predictor
4.7 Moment structure of the latent variables
4.8 Marginal moment structure of observed and latent responses
4.9Re duced form distribution and likelihood
4.10 Reduced form parameters
4.11 Summary and further reading
5 Identification and equivalence
5.1 Introduction
5.2 Identification
5.3 Equivalence
5.4 Summary and further reading
6 Estimation
6.1 Introduction
6.2 Maximum likelihood: Closed form marginal likelihood
6.3 Maximum likelihood: Approximate marginal likelihood
6.4 Maximizing the likelihood
6.5 Nonparametric maximum likelihood estimation
6.6 Restricted/Residual maximum likelihood (REML)
6.7 Limited information methods
6.8 Maximum quasi-likelihood
6.9G eneralized Estimating Equations (GEE)
6.10 Fixed effects methods
6.11 Bayesian methods
6.12 Summary
Appendix: Some software and references
7 Assigning values to latent variables
7.1 Introduction
7.2 Posterior distributions
7.3 Empirical Bayes (EB)
7.4 Empirical Bayes modal (EBM)
7.5 Maximum likelihood
7.6 Relating the scoring methods in the ‘linear case’
7.7 Ad hoc scoring methods
7.8 Some uses of latent scoring and classification
7.9S ummary and further reading

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关键词：Generalized Generalize Modeling Variable General different values

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