Results 11 to 20 of about 1,871,607 (274)
Probing Beyond: The Impact of Model Size and Prior Informativeness on Bayesian SEM Fit Indices [PDF]
Behavior Research MethodsAbstract Examining how well a hypothesized model fits observed data is pivotal in Bayesian structural equation modeling (SEM). Recent efforts have aimed to formulate Bayesian SEM fit indices akin to those used in frequentist SEM. However, the assessment of these fit indices in Bayesian SEM has been limited in scope. This research entailed two
Xinya Liang, Chunhua Cao, Ejike Edeh
exaly +4 more sources
The SEM Reliability Paradox in a Bayesian Framework
Structural Equation Modeling: A Multidisciplinary Journal, 2023 Within the frequentist structural equation modeling (SEM) framework, adjudicating model quality through measures of fit has been an active area of methodological research. Complicating this conversation is research revealing that a higher quality measurement portion of a SEM can result in poorer estimates of overall model fit than lower quality ...
Timothy R. Konold, Elizabeth A. Sanders
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Impact analysis of institutional framework and policy preferences with Bayesian structural equation. [PDF]
PLoS ONEMediation analysis is able to deeply analyze the finer mechanism of the path of exposure variables leading to outcome variables and has received extensive attention in many fields in recent years.
Song Jin +3 more
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Sequential Bayesian SEM for Task Technology Fit
International Journal of Advanced Research in Computer ScienceThe Task Technology Fit (TTF) model is a key framework in information systems research that examines the relationship between user task needs and technological capabilities. Structural Equation Modeling (SEM) and Bayesian Structural Equation Modeling (BSEM) are effective tools for analyzing the TTF model.
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MethodologyIn social sciences, researchers often compare relations between constructs, referred to as “structural relations”, across a large number of groups. This paper proposes Mixture Multigroup Bayesian SEM (MixMG-BSEM), a novel method for comparing structural ...
Hongwei Zhao +2 more
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Efficient Bayesian Structural Equation Modeling in Stan
Journal of Statistical Software, 2021 Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof.
Edgar C. Merkle +3 more
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Opaque Prior Distributions in Bayesian Latent Variable Models
Methodology, 2023 We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation.
Edgar C. Merkle +3 more
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Bayesian Approximations to Hidden Semi-Markov Models for Telemetric Monitoring of Physical Activity [PDF]
, 2022 We propose a Bayesian hidden Markov model for analyzing time series and sequential data where a special structure of the transition probability matrix is embedded to model explicit-duration semi-Markovian dynamics.
Fiecas, Mark +5 more
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G3: Genes, Genomes, Genetics, 2020 Bayesian regression methods that incorporate different mixture priors for marker effects are used in multi-trait genomic prediction. These methods can also be extended to genome-wide association studies (GWAS).
Zigui Wang +3 more
doaj +1 more source
The Effect of Risk Dimensions on the Objectives of Construction Projects in Isfahan Municipality: An Integrated SEM and BBN Analysis [PDF]
مدیریت بهره وری, 2021 Population growth and the subsequent surge in urbanization has drastically increased the number of construction projects in metropolitan cities implementation and management of which may involve numerous ambiguous and unknown issues or risks that can ...
Amir Hossein Nadali Jelokhani +3 more
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