Parsimonious structural equation models for repeated measures data, with application to the study of consumer preferences

DOI10.1007/s11336-012-9260-xzbMath1284.62702OpenAlexW2034961489MaRDI QIDQ418423

Terry Elrod, Gerald Häubl, Steven W. Tipps

Publication date: 29 May 2012

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-012-9260-x

zbMATH Keywords

singular value decompositionrandom coefficientsrandom effectsstructural equation modelsreduced-rank regressionmultilevel modelsconjoint analysisconsumer preferencesLu decompositionmatrix approximationmultilevel latent variable modelssecond-order factor analysis

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Uses Software

• Mplus
• LISREL

Cites Work

• A hierarchical Ornstein-Uhlenbeck model for continuous repeated measurement data
• Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
• Factor analysis and AIC
• On the choice of a model to fit data from an exponential family
• Nonlinear estimation
• Reduced-rank regression for the multivariate linear model
• Estimating the dimension of a model
• Multivariate reduced-rank regression
• Marketing models of consumer heterogeneity
• STEMM: A general finite mixture structural equation model
• Rank estimation in reduced-rank regression
• A multivariate reduced-rank growth curve model with unbalanced data
• Evolutionary preference/utility functions: a dynamic perspective
• Some contributions to maximum likelihood factor analysis
• An Extended Multivariate Random-Effects Growth Curve Model
• Applied Linear Algebra and Matrix Analysis
• Bayesian Measures of Model Complexity and Fit
• 8 Some Matrix Results Useful in Psychometric Research
• Factor Analysis
• 10 Structural Equation Modeling
• 12 Multilevel Models in Psychometrics
• 13 Latent Class Analysis in Psychometrics
• 14 Random-Effects Models for Preference Data
• Conditional Akaike information for mixed-effects models
• Efficient Inference in a Random Coefficient Regression Model
• A new look at the statistical model identification
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Parsimonious structural equation models for repeated measures data, with application to the study of consumer preferences