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2008-06-15
220175.rar
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220176.rar
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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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2008-6-15 20:01:00

Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models (Hardcover)

by Anders Skrondal (Author), Sophia Rabe-Heske

  • Hardcover: 512 pages
  • Publisher: Chapman & Hall/CRC; 1 edition (May 6, 2004)
  • Language: English
  • ISBN-10: 1584880007
  • ISBN-13: 978-1584880004
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    2008-6-15 20:05:00

    Generalized Latent Variable Modeling

    Skrondal, A. and Rabe-Hesketh, S. (2004). Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models. Chapman & Hall/CRC.


    Full Table of Contents
    Remarks and corrections
    Worked examples
    Reviews

    zip-file with all datasets (plain text), Stata do-files & readme file

    Data by Section: Application Chapters (Part II)

    • Chapter 9: Dichotomous responses
      • 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
    • Chapter 11: Counts
      • 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
    • Chapter 12: Durations and survival
      • 12.4 Exercise and angina: Proportional hazards random effects and factor models
    • Chapter 13: Comparative responses
      • 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
    • Chapter 14: Multiple processes and mixed responses
      • 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 chirrosis: A joint survival and marker model
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      2008-7-14 22:05:00
      楼主我购买了你的书,但是下载不了。能否给我email 一份或者更新你的文件。谢谢
      bulluson@gmail.com
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      2008-7-15 08:10:00
      楼主牛啊 不过怎么电子版和我复印的版本页数不一样呢 差个20多页
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      2008-9-27 16:50:00
      楼主,请问购买后如何下载?十分感谢!
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