Generalized Latent Variable Modeling

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A01=Anders Skrondal
A01=Sophia Rabe-Hesketh
Adaptive Quadrature
Author_Anders Skrondal
Author_Sophia Rabe-Hesketh
Baseline Hazard
bayes
Category=PBWH
class
Conditional Expectation
Covariance Matrix
Covariate Measurement Error Models
discrete
Discrete Latent Variables
dummy
Dummy Variable
educational statistics applications
empirical
Empirical Bayes Predictions
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
finite mixture estimation
Generalized Linear Mixed Models
Generalized Linear Model
intercept
IRT Model
Item Response Model
joint modeling of survival and longitudinal data
Latent Class Model
Latent Variable Modeling
Latent Variables
Linear Mixed Models
Linear Predictor
longitudinal data modeling
Mimic Model
multilevel analysis
nonparametric
Norwegian Social Science Data Services
Posterior Distribution
predictions
Proportional Odds Model
psychometric methods
random
Random Intercept
Random Intercept Model
Reduced Form Parameters
survival analysis techniques
Unobserved Heterogeneity
variables

Product details

  • ISBN 9781584880004
  • Weight: 1130g
  • Dimensions: 156 x 234mm
  • Publication Date: 11 May 2004
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models. Following a gentle introduction to latent variable modeling, the authors clearly explain and contrast a wide range of estimation and prediction methods from biostatistics, psychometrics, econometrics, and statistics. They present exciting and realistic applications that demonstrate how researchers can use latent variable modeling to solve concrete problems in areas as diverse as medicine, economics, and psychology. The examples considered include many nonstandard response types, such as ordinal, nominal, count, and survival data. Joint modeling of mixed responses, such as survival and longitudinal data, is also illustrated. Numerous displays, figures, and graphs make the text vivid and easy to read.

About the authors:

Anders Skrondal is Professor and Chair in Social Statistics, Department of Statistics, London School of Economics, UK

Sophia Rabe-Hesketh is a Professor of Educational Statistics at the Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA.

Anders Skrondal, Sophia Rabe-Hesketh

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