Open Access
Multilevel Latent Variable Modeling
About:
The article was published on 2010-02-01 and is currently open access. It has received 6 citations till now. The article focuses on the topics: Latent variable model.read more
Citations
More filters
Journal ArticleDOI
Clusterwise simultaneous component analysis for analyzing structural differences in multivariate multiblock data.
Kim De Roover,Eva Ceulemans,Marieke E. Timmerman,Kristof Vansteelandt,Jeroen Stouten,Patrick Onghena +5 more
TL;DR: The key idea behind clusterwise SCA is that the data blocks form a few clusters, where data blocks that belong to the same cluster are modeled with SCA and thus have the same structure, and different clusters have different underlying structures.
Journal ArticleDOI
Parameter Specification in Bayesian CFA: An Exploration of Multivariate and Separation Strategy Priors
TL;DR: The main goal of these studies was to examine the impact of different parameter specifications, as crossed with different forms of prior distributions, on the accuracy of parameter estimates–examined via relative bias.
Bayesian Modeling of Measurement Error in Predictor Variables Using Item Response Theory. Research Report.
Jean-Paul Fox,Cees A. W. Glas +1 more
TL;DR: In this paper, it is shown that measurement error in predictor variables can be modeled using item response theory (IRT) and the predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables.
Journal ArticleDOI
Reconsidering Cluster Bias in Multilevel Data: A Monte Carlo Comparison of Free and Constrained Baseline Approaches.
TL;DR: A Monte Carlo study investigated the improvement in model fit that results from freeing an item's between level residual variance from a baseline model with equal within and between level factor loadings and betweenlevel residual variances fixed at zero and recommended a free baseline approach when the referent indicator is biased.
Cluster bias: Testing measurement invariance in multilevel data
TL;DR: In this paper, the authors present methods and procedures to test and account for measurement bias in multilevel data with a clustered structure, for instance data of children grouped in classrooms, or data of employees in teams.
References
More filters
Book
Multilevel Analysis: Techniques and Applications
TL;DR: This work focuses on the development of a single model for Multilevel Regression, which has been shown to provide good predictive power in relation to both the number of cases and the severity of the cases.
Journal ArticleDOI
A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
Journal ArticleDOI
Estimation of latent ability using a response pattern of graded scores
TL;DR: In this article, the authors considered the problem of estimating latent ability using the entire response pattern of free-response items, first in the general case and then in the case where the items are scored in a graded way, especially when the thinking process required for solving each item is assumed to be homogeneous.
Journal ArticleDOI
A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators
TL;DR: In this paper, a structural equation model with a generalized measurement part was proposed for dichotomous and ordered categorical variables (indicators) in addition to continuous ones, and a computationally feasible three-stage estimator is proposed for any combination of observed variable types.
Book
Finite Mixture and Markov Switching Models
TL;DR: This book should help newcomers to the field to understand how finite mixture and Markov switching models are formulated, what structures they imply on the data, what they could be used for, and how they are estimated.
Related Papers (5)
Multiple Group Analysis in Multilevel Data Across Within-Level Groups: A Comparison of Multilevel Factor Mixture Modeling and Multilevel Multiple-Indicators Multiple-Causes Modeling.
Sookyoung Son,Sehee Hong +1 more
Bayesian estimation of single and multilevel models with latent variable interactions
Tihomir Asparouhov,Bengt Muthén +1 more