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Implementation Aspects in Regularized Structural Equation Models
This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non ...
Alexander Robitzsch
doaj +1 more source
Semiparametric Bayesian inference in multiple equation models [PDF]
This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components.
Poirier, Dale J. +2 more
core +4 more sources
Bayesian Structural Equation Envelope Model
Abstract The envelope model has gained significant attention since its proposal, offering a fresh perspective on dimension reduction in multivariate regression models and improving estimation efficiency. One of its appealing features is its adaptability to diverse regression contexts.
Chuchu Wang +3 more
openaire +3 more sources
Dynamic structural equation modeling (DSEM) is a novel, intensive longitudinal data (ILD) analysis framework. DSEM models intraindividual changes over time on Level 1 and allows the parameters of these processes to vary across individuals on Level 2 ...
Schultzberg, Mårten, +3 more
core +1 more source
Applying SEM, Exploratory SEM, and Bayesian SEM to Personality Assessments
Despite the importance of demonstrating and evaluating how structural equation modeling (SEM), exploratory structural equation modeling (ESEM), and Bayesian structural equation modeling (BSEM) work simultaneously, research comparing these analytic ...
Hyeri Hong +2 more
doaj +1 more source
How few countries will do? Comparative survey analysis from a Bayesian perspective
Meuleman and Billiet (2009) have carried out a simulation study aimed at the question how many countries are needed for accurate multilevel SEM estimation in comparative studies.
Joop J.C.M. Hox +2 more
doaj +1 more source
HYPER-PARAMETER SELECTION IN BAYESIAN STRUCTURAL EQUATION MODELS [PDF]
Summary: In the structural equation models, the maximum likelihood estimates of error variances can often turn out to be zero or negative. In order to overcome this problem, we take a Bayesian approach by specifying a prior distribution for variances of error variables. Crucial issues in this modeling procedure include the selection of hyper-parameters
Hirose, Kei +3 more
openaire +2 more sources
Bayesian estimation of latent variable models provides some unique advantages to researchers working with small samples and complex models when compared with the more commonly used maximum likelihood approach.
Holmes Finch
doaj +1 more source
In this study, a novel esterase from the thermoacidophilic archaeon Thermoplasma acidophilum was biochemically and structurally characterized. Our results demonstrate that Ta0887 is a highly thermostable esterase that preferentially hydrolyzes p‐nitrophenyl hexanoate and possesses an α‐helical cap domain that likely contributes to its substrate ...
Alejandro Delgado‐Rey +4 more
wiley +1 more source
Subjective Cognitive Concerns and Cognitive Trajectories in Parkinson's Disease: Biomarker Impact
ABSTRACT Objective To examine the relationship of subjective cognitive concerns (SCC) with biomarkers of Alzheimer's disease (AD), neurodegeneration, and Parkinson's disease (PD) and domain‐specific cognitive trajectories among cognitively unimpaired persons with de novo PD. Method Cognitively unimpaired participants with SCC (n = 294) and without SCC (
Francesca V. Lopez +5 more
wiley +1 more source

