Jenni Niku, David I. Warton, Francis K.C. Hui, and Sara Taskinen (2017). Generalized Linear Latent Variable Models for Multivariate Abundance Data in Ecology. The Journal of Agricultural, Biological and Environmental Statistics.Niku J, Warton, DI, Hui Francis K.C, Taskinen S. 2017. ...
gllvmis an R package for analysing multivariate ecological data with Generalized Linear Latent Variable Models (GLLVM). Estimation is performed using maximum likelihood estimation, together with either variational approximation (VA) or Laplace approximation (LA) method to approximate the marginal likelihood...
Monte Carlo methods/ generalized linear latent variable modelingmulti-group studieslatent common factorspolytomous responsesmulti-sample latent variable analysismaximum likelihood analysisLatent variable modeling is commonly used in behavioral, social, and medical science research. The models used in such ...
Recently, generalized linear latent variable models for categorical, metric, and mixed-type responses estimated via maximum likelihood (ML) have been proposed. Model deviations, such as data contamination, are shown analytically, using the influence function and through a simulation study, to seriously...
Latent variable models represent a useful tool for the analysis of complex data when the constructs of interest are not observable. A problem related to these models is that the integrals involved in the likelihood function cannot be solved analytically. We propose a computational approach, referred...
Parameter constraints in generalized linear latent variable models are discussed. Both linear equality and inequality constraints are considered. Maximum l... R Tsonaka,I Moustaki - 《Computational Statistics & Data Analysis》 被引量: 54发表: 2007年 Variance Component Testing in Generalized Linear Mixe...
This paper proposes a robust estimator for a general class of linear latent variable models (GLLVM) (Moustaki and Knott 2000, Bartholomew and Knott 1999). It is based on a weighted score function that is simple to implement numerically and is made consistent using the basic idea of indirect ...
Generalized Linear Latent Variables Models (GLLVM) enable the modeling of relationships between manifest and latent variables, where the manifest variables are distributed according to a distribution of the exponential family (e.g., binomial or normal) and to the multinomial distribution (for ordinal ...
Wilson and Generalized Latent Variable Modeling: Multilevel, Longitudinal and Structural Equation Models by A. Skrondal and S. Rabe-Hesketh 来自 EconPapers 喜欢 0 阅读量: 82 作者: J Verkuilen 摘要: No abstract is available for this item. DOI: 10.1007/s11336-005-1333-7 被引量: 4 ...
Latent variable models are commonly used in medical statistics, although often not referred to under this name. In this paper we describe classical latent variable models such as factor analysis, item response theory, latent class models and structural equation models. Their usefulness in medical rese...