Generalized latent variable modeling : multilevel, longitudinal, and structural equation models /
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| Author / Creator: | Skrondal, Anders. |
|---|---|
| Imprint: | Boca Raton : Chapman & Hall/CRC, c2004. |
| Description: | xi, 508 p. : ill. ; 25 cm. |
| Language: | English |
| Series: | Chapman & Hall/CRC interdisciplinary statistics series Interdisciplinary statistics. |
| Subject: | |
| Format: | Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/5171970 |
Table of Contents:
- 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
- 1.9. Summary
- 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
- 4. General 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
- 4.9. Reduced 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
- 6.9. Generalized 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
- 7.9. Summary and further reading
- Appendix. Some software
- 8. Model specification and inference
- 8.1. Introduction
- 8.2. Statistical modeling
- 8.3. Inference (likelihood based)
- 8.4. Model selection: Relative fit criteria
- 8.5. Model adequacy: Global absolute fit criteria
- 8.6. Model diagnostics: Local absolute fit criteria
- 8.7. Summary and further reading
- II. Applications
- 9. Dichotomous responses
- 9.1. Introduction
- 9.2. Respiratory infection in children: A random intercept model
- 9.3. Diagnosis of myocardial infarction: A latent class model
- 9.4. Arithmetic reasoning: Item response models
- 9.5. Nicotine gum and smoking cessation: A meta-analysis
- 9.6. Wives' employment transitions: Markov models with unobserved heterogeneity
- 9.7. Counting snowshoe hares: Capture-recapture models with heterogeneity
- 9.8. Attitudes to abortion: A multilevel item response model
- 9.9. Summary and further reading
- 10. Ordinal responses
- 10.1. Introduction
- 10.2. Cluster randomized trial of sex education: Latent growth curve model
- 10.3. Political efficacy: Factor dimensionality and item-bias
- 10.4. Life satisfaction: Ordinal scaled probit factor models
- 10.5. Summary and further reading
- 11. Counts
- 11.1. Introduction
- 11.2. Prevention of faulty teeth in children: Modeling overdispersion
- 11.3. Treatment of epilepsy: A random coefficient model
- 11.4. Lip cancer in Scotland: Disease mapping
- 11.5. Summary and further reading
- 12. Durations and survival
- 12.1. Introduction
- 12.2. Modeling multiple events clustered duration data
- 12.3. Onset of smoking: Discrete time frailty models
- 12.4. Exercise and angina: Proportional hazards random effects and factor models
- 12.5. Summary and further reading
- 13. Comparative responses
- 13.1. Introduction
- 13.2. Heterogeneity and 'Independence from Irrelevant Alternatives'
- 13.3. Model structure
- 13.4. British general elections: Multilevel models for discrete choice and rankings
- 13.5. Post-materialism: A latent class model for rankings
- 13.6. Consumer preferences for coffee makers: A conjoint choice model
- 13.7. Summary and further reading
- 14. Multiple processes and mixed responses
- 14.1. Introduction
- 14.2. Diet and heart disease: A covariate measurement error model
- 14.3. Herpes and cervical cancer: A latent class covariate measurement error model for a case-control study
- 14.4. Job training and depression: A complier average causal effect model
- 14.5. Physician advice and drinking: An endogenous treatment model
- 14.6. Treatment of liver cirrhosis: A joint survival and marker model
- 14.7. Summary and further reading
- References
- Index
- Author index
