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Dynamic Structural Equation Models

Structural Equation Modeling: A Multidisciplinary Journal, 2017
This article presents dynamic structural equation modeling (DSEM), which can be used to study the evolution of observed and latent variables as well as the structural equation models over time. DSEM is suitable for analyzing intensive longitudinal data where observations from multiple individuals are collected at many points in time.
Asparouhov, T., Hamaker, E.L., Muthen, Bengt   +2 more
openaire   +3 more sources

Number of Subjects and Time Points Needed for Multilevel Time-Series Analysis: A Simulation Study of Dynamic Structural Equation Modeling

, 2017
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,, Mårten Schultzberg, Bengt Muthén, Muthen, Bengt,   +3 more
core   +1 more source

An evaluation of non-iterative estimators in the structural after measurement (SAM) approach to structural equation modeling (SEM)

, 2023
In Structural Equation Modeling (SEM), the measurement part and the structural part are typically estimated simultaneously via an iterative Maximum Likelihood (ML) procedure.
Dhaene, SaraUGent0001305283518020030958519737864428900000-0003-0347-831X60301E54-0B76-11E3-A15D-175D10BDE39D, Rosseel, YvesPP018010009749090000-0002-4129-4477F4D626CE-F0ED-11E1-A9DE-61C894A0A6B4   +1 more
core  

WILL DIGITAL BANKING TRANSFORMATION AFFECT CONSUMER BEHAVIOR IN THE FINANCIAL SECTOR? [PDF]

Journal of Applied Structural Equation Modeling
This study aims to examine how customer communication, trustworthiness, transparency, and innovation influence the transformation of digital banking. It also investigates the impact of digital banking transformation on customers’ financial behavior. Data
Darwis Harahap, Ahmad Afandi, Try Mahendra Siregar, Abdul Nasser Hasibuan, Utari Evy Cahyahni   +4 more
doaj   +1 more source

Estimating and Testing Random Intercept Multilevel Structural Equation Models with Model Implied Instrumental Variables

, 2022
This study develops a new limited information estimator for random intercept Multilevel Structural Equation Models (MSEM). It is based on the Model Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) estimator, which has been shown to be an
Bollen, Kenneth A.,, Giordano, Michael L.,, Jin, Shaobo,   +2 more
core   +1 more source

Structural insights into an engineered feruloyl esterase with improved MHET degrading properties

FEBS Letters, EarlyView.
A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa, Konstantinos Makryniotis, Theofani‐Iosifina Sousani, Evangelos Topakas, Vangelis Daskalakis, Maria Dimarogona   +5 more
wiley   +1 more source

Ecopreneurship, GenAI, Digital Green Orientation, and Environmental Performance in Software Firms [PDF]

Journal of Applied Structural Equation Modeling
This paper is grounded in the natural resource-based view to investigate the role of ecopreneurship in enhancing the environmental performance of software firms.
Muhammad Usman Siddqiue, Muhammad Zia Aslam, Sarfraz Zaman   +2 more
doaj   +1 more source

Valosin‐containing protein counteracts ATP‐driven dissolution of FUS condensates through its ATPase activity in vitro

FEBS Letters, EarlyView.
Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura, Shin‐ichi Tate, Kyota Yasuda   +2 more
wiley   +1 more source

Learning Structural Equation Models for fMRI [PDF]

, 2007
Structural equation models can be seen as an extension of Gaussian belief networks to cyclic graphs, and we show they can be understood generatively as the model for the joint distribution of long term average equilibrium activity of Gaussian dynamic belief networks.
Simonotto, Enrico, Whalley, Heather; id_orcid 0000-0002-4505-8869, Lawrie, Stephen, Murray, Lawrence, Mcgonigle, David, Storkey, Amos J   +5 more
openaire   +3 more sources

Data Smoothing Structural Equation Modeling to Study Quality of Life and Model Selection

, 2023
In this paper, we propose and present a nonparametric data smoothing method via the kernel smoothing functions to make structural equation modeling (SEM) robust to a specific type of model misspecification, that is an incorrect distributional assumption.
Hamparsum Bozdogan, Deniz, Eylem, Bozdogan, Hamparsum, Eylem Deniz   +3 more
core   +1 more source