Results 21 to 30 of about 7,097,824 (285)

Data-Driven Path Analytic Modeling to Understand Underlying Mechanisms in COVID-19 Survivors Suffering from Long-Term Post-COVID Pain: A Spanish Cohort Study

Pathogens, 2022
Pain can be present in up to 50% of people with post-COVID-19 condition. Understanding the complexity of post-COVID pain can help with better phenotyping of this post-COVID symptom.
César Fernández-de-las-Peñas, Bernard X. W. Liew, Manuel Herrero-Montes, Pablo del-Valle-Loarte, Rafael Rodríguez-Rosado, Diego Ferrer-Pargada, Randy Neblett, Paula Paras-Bravo   +7 more
doaj   +1 more source

A semiparametric approach for structural equation modeling with ordinal data

, 2021
There is currently a lack of methods for non-linear structural equation modeling (NSEM) for non-parametric relationships between latent variables when data are ordinal. To this end, a semiparametric approach for flexible NSEMs without parametric forms is
Vegelius, Johan, Jin, Shaobo, Vegelius, Johan,, Jin, Shaobo,, Johan Vegelius, Shaobo Jin   +5 more
core   +1 more source

A theory-based and data-driven approach to promoting physical activity through message-based interventions

Frontiers in Psychology, 2023
ObjectiveWe investigated how physical activity can be effectively promoted with a message-based intervention, by combining the explanatory power of theory-based structural equation modeling with the predictive power of data-driven artificial intelligence.
Patrizia Catellani, Marco Biella, Valentina Carfora, Antonio Nardone, Luca Brischigiaro, Marina Rita Manera, Marco Piastra   +6 more
doaj   +1 more source

The Construction of Patient Loyalty Model Using Bayesian Structural Equation Modeling Approach

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2018
The information on the health status of an individual is often gathered based on a health survey. Patient assessment on the quality of hospital services is important as a reference in improving the service so that it can increase a patient satisfaction ...
Astari Rahmadita, Ferra Yanuar, Dodi Devianto   +2 more
doaj   +1 more source

Gaussian Process Panel Modeling—Machine Learning Inspired Analysis of Longitudinal Panel Data

Frontiers in Psychology, 2020
In this article, we extend the Bayesian nonparametric regression method Gaussian Process Regression to the analysis of longitudinal panel data. We call this new approach Gaussian Process Panel Modeling (GPPM).
Julian D. Karch, Julian D. Karch, Andreas M. Brandmaier, Andreas M. Brandmaier, Manuel C. Voelkle   +4 more
doaj   +1 more source

Using the Effective Sample Size as the Stopping Criterion in Markov Chain Monte Carlo with the Bayes Module in Mplus

Psych, 2021
Bayesian modeling using Markov chain Monte Carlo (MCMC) estimation requires researchers to decide not only whether estimation has converged but also whether the Bayesian estimates are well-approximated by summary statistics from the chain.
Steffen Zitzmann, Sebastian Weirich, Martin Hecht   +2 more
doaj   +1 more source

Improving Service Quality of Metro Systems—A Case Study in the Beijing Metro

IEEE Access, 2020
In this study, we propose a method that combines Bayesian network, structural equation modeling, and importance-performance analyses to evaluate and improve the service quality of crowded metros from the point of service components.
Xinyue Xu, Yi Lu, Yingxiang Wang, Jianmin Li, Hanyu Zhang   +4 more
doaj   +1 more source

Bayesian regularized quantile structural equation models

Journal of Multivariate Analysis, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiang-Nan Feng, Yifan Wang, Bin Lu, Xinyuan Song 0001   +3 more
openaire   +1 more source

Prior Specification for More Stable Bayesian Estimation of Multilevel Latent Variable Models in Small Samples: A Comparative Investigation of Two Different Approaches

Frontiers in Psychology, 2021
Bayesian approaches for estimating multilevel latent variable models can be beneficial in small samples. Prior distributions can be used to overcome small sample problems, for example, when priors that increase the accuracy of estimation are chosen. This
Steffen Zitzmann, Christoph Helm, Martin Hecht   +2 more
doaj   +1 more source

Exploratory Structural Equation Modeling of Personality Data [PDF]

, 2014
The current article compares the use of exploratory structural equation modeling (ESEM) as an alternative to confirmatory factor analytic (CFA) models in personality research.
Hughes, David; id_orcid, Hughes, David J, Booth, Tom   +2 more
core   +1 more source