Unified structural equation modeling (uSEM) implemented in the group iterative multiple model estimation (GIMME) framework has recently been widely used for characterizing within-person network dynamics of behavioral and functional neuroimaging variables. Previous studies have established that GIMME accurately recovers the presence of relations between variables. However, recovery of relation directionality is less consistent, which is concerning given the importance of directionality estimates for many research questions. There is evidence that strong autoregressive relations may aid directionality recovery and indirect evidence that a novel version of GIMME allowing for multiple solutions could improve recovery when such relations are weak, but it remains unclear how these strategies perform under a range of study conditions. Using comprehensive simulations that varied the strength of autoregressive relations among other factors, this study evaluated the directionality recovery of two GIMME search strategies: (a) estimating autoregressive relations by default in the null model (GIMME-AR) and (b) generating multiple solution paths (GIMME-MS). Both strategies recovered directionality best-and were roughly equivalent in performance-when autoregressive relations were strong (e.g., β = .60). When they were weak (β ≤ .10), GIMME-MS displayed an advantage, although overall directionality recovery was modest. Analyses of empirical data in which autoregressive relations were characteristically strong (resting state functional MRI) versus weak (daily diary) mirrored simulation results and confirmed that these strategies can disagree on directionality when autoregressive relations are weak. Findings have important implications for psychological and neuroimaging applications of uSEM/GIMME and suggest specific scenarios in which researchers might or might not be confident in directionality results. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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http://dx.doi.org/10.1037/met0000460 | DOI Listing |
Alcohol Clin Exp Res (Hoboken)
January 2025
Department of Psychology, University of Amsterdam, Amsterdam, Noord-Holland, The Netherlands.
Background: The complex interactions between an individual's drinking behavior and their social environment is crucial but understudied, particularly in mature adult populations. Our aim is to unravel these complexities by investigating how personal drinking patterns are related to those of one's social environment over time, and what the interplay is with personal factors such as occupational prestige and smoking behavior.
Method: The present study adopts an innovative graphical autoregressive (GVAR) panel network modeling approach to investigate the dynamics between personal drinking habits and social environmental factors, utilizing a comprehensive longitudinal dataset from the Framingham Heart Study with a large sample of predominantly mature adults (N = 1719-5718) connected within a social network.
J Aquat Anim Health
December 2024
Department of Health Management and Centre for Veterinary Epidemiological Research, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada.
Objective: The primary objective was to construct a time series model for the abundance of the adult female (AF) sea lice Lepeophtheirus salmonis in Atlantic Salmon Salmo salar farms in the Bay of Fundy, New Brunswick, Canada, for the period 2016-2021 and to illustrate its short-term predictive capabilities.
Methods: Sea lice are routinely counted for monitoring purposes, and these data are recorded in the Fish-iTrends database. A multivariable autoregressive linear mixed-effects model (second-order autoregressive structure) was generated with the outcome of the abundance of AF sea lice and included treatments, infestation pressures (a measure that represents the dose of exposure of sea louse parasitic stages to potential fish hosts) within sites (internal) and among sites (external), and other predictors.
Psychol Med
December 2024
Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
Background: Loneliness has become a major public health issue of the recent decades due to its severe impact on health and mortality. Little is known about the relation between loneliness and social anxiety. This study aimed (1) to explore levels of loneliness and social anxiety in the general population, and (2) to assess whether and how loneliness affects symptoms of social anxiety and vice versa over a period of five years.
View Article and Find Full Text PDFInt J Health Care Qual Assur
December 2024
Institute of Management Studies, Devi Ahilya Vishwavidyalaya, Indore, India.
Purpose: From poor healthcare infrastructure to vaccine donors, India has traveled a long way. In this study, the author tried to find the investment certainty and persistence of volatility in the Indian healthcare system due to COVID-19.
Design/methodology/approach: Using the Generalized Autoregressive Conditional Heteroskedasticity (GARCH 1,1) model, this study quantifies the change in the conditional variance after the first case report of COVID-19.
J Adolesc
December 2024
Department of Psychology, Università degli studi di Torino, Turin, Italy.
Introduction: Recent evidence demonstrates an association between social media addiction (SMA) and aggressive behaviors; however, the longitudinal relationship between these two variables remains not fully understood. The aim of this study was to examine the longitudinal relationship between SMA and aggressive behaviors (overt and relational aggression) in early adolescence and to identify gender differences in this relationship.
Methods: A sample of 568 Italian early adolescents (52.
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