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Harari, Ofir; Soltanifar, Mohsen; Cappelleri, Joseph C.; Verhoek, Andre; Ouwens, Mario; Daly, Caitlin; Heeg, Bart – Research Synthesis Methods, 2023
Effect modification (EM) may cause bias in network meta-analysis (NMA). Existing population adjustment NMA methods use individual patient data to adjust for EM but disregard available subgroup information from aggregated data in the evidence network. Additionally, these methods often rely on the shared effect modification (SEM) assumption. In this…
Descriptors: Networks, Network Analysis, Meta Analysis, Evaluation Methods
Hongxi Li; Shuwei Li; Liuquan Sun; Xinyuan Song – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…
Descriptors: Statistical Analysis, Statistical Studies, Structural Equation Models, Intervals
Andrea Hasl; Manuel Voelkle; Charles Driver; Julia Kretschmann; Martin Brunner – Structural Equation Modeling: A Multidisciplinary Journal, 2024
To examine developmental processes, intervention effects, or both, longitudinal studies often aim to include measurement intervals that are equally spaced for all participants. In reality, however, this goal is hardly ever met. Although different approaches have been proposed to deal with this issue, few studies have investigated the potential…
Descriptors: Foreign Countries, Elementary School Students, Secondary School Students, Student Promotion
Liang, Xinya – Educational and Psychological Measurement, 2020
Bayesian structural equation modeling (BSEM) is a flexible tool for the exploration and estimation of sparse factor loading structures; that is, most cross-loading entries are zero and only a few important cross-loadings are nonzero. The current investigation was focused on the BSEM with small-variance normal distribution priors (BSEM-N) for both…
Descriptors: Factor Structure, Bayesian Statistics, Structural Equation Models, Goodness of Fit
Pek, Jolynn; Chalmers, R. Philip; Kok, Bethany E.; Losardo, Diane – Journal of Educational and Behavioral Statistics, 2015
Structural equation mixture models (SEMMs), when applied as a semiparametric model (SPM), can adequately recover potentially nonlinear latent relationships without their specification. This SPM is useful for exploratory analysis when the form of the latent regression is unknown. The purpose of this article is to help users familiar with structural…
Descriptors: Structural Equation Models, Nonparametric Statistics, Regression (Statistics), Maximum Likelihood Statistics
Adolescents' Religiousness and Substance Use Are Linked via Afterlife Beliefs and Future Orientation
Holmes, Christopher; Kim-Spoon, Jungmeen – Journal of Early Adolescence, 2017
Although religiousness has been identified as a protective factor against adolescent substance use, processes through which these effects may operate are unclear. The current longitudinal study examined sequential mediation of afterlife beliefs and future orientation in the relation between adolescent religiousness and cigarette, alcohol, and…
Descriptors: Religion, Beliefs, Role, Correlation
Raykov, Tenko; Marcoulides, George A. – Structural Equation Modeling: A Multidisciplinary Journal, 2013
A latent variable modeling approach is outlined that can be used for meta-analysis of reliability coefficients of multicomponent measuring instruments. Important limitations of efforts to combine composite reliability findings across multiple studies are initially pointed out. A reliability synthesis procedure is discussed that is based on…
Descriptors: Meta Analysis, Reliability, Structural Equation Models, Error of Measurement
Zhang, Dongbo; Koda, Keiko; Leong, Che Kan – Reading and Writing: An Interdisciplinary Journal, 2016
This longitudinal study examined the contribution of morphological awareness to bilingual word learning of Malay-English bilingual children in Singapore where English is the medium of instruction. Participants took morphological awareness and lexical inference tasks in both English and Malay twice with an interval of about half a year, the first…
Descriptors: Foreign Countries, Morphology (Languages), Bilingual Education, Bilingualism
Li, Xin; Beretvas, S. Natasha – Structural Equation Modeling: A Multidisciplinary Journal, 2013
This simulation study investigated use of the multilevel structural equation model (MLSEM) for handling measurement error in both mediator and outcome variables ("M" and "Y") in an upper level multilevel mediation model. Mediation and outcome variable indicators were generated with measurement error. Parameter and standard…
Descriptors: Sample Size, Structural Equation Models, Simulation, Multivariate Analysis
Sideridis, Georgios; Simos, Panagiotis; Papanicolaou, Andrew; Fletcher, Jack – Educational and Psychological Measurement, 2014
The present study assessed the impact of sample size on the power and fit of structural equation modeling applied to functional brain connectivity hypotheses. The data consisted of time-constrained minimum norm estimates of regional brain activity during performance of a reading task obtained with magnetoencephalography. Power analysis was first…
Descriptors: Structural Equation Models, Brain Hemisphere Functions, Simulation, Models
Overbeek, Geertjan; Zeevalkink, Herma; Vermulst, Ad; Scholte, Ron H. J. – Social Development, 2010
This study examined bidirectional, longitudinal associations between peer victimisation and self-esteem in adolescents, and tested for moderator effects of undercontrolling, overcontrolling, and ego-resilient personality types in these associations. Data were used from 774 adolescents ages 11-16 years who participated in a three-wave (i.e., 2005,…
Descriptors: Intervals, Self Concept, Peer Relationship, Personality Traits
Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
Ecker, Ullrich K. H.; Lewandowsky, Stephan; Oberauer, Klaus; Chee, Abby E. H. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2010
Working memory updating (WMU) has been identified as a cognitive function of prime importance for everyday tasks and has also been found to be a significant predictor of higher mental abilities. Yet, little is known about the constituent processes of WMU. We suggest that operations required in a typical WMU task can be decomposed into 3 major…
Descriptors: Structural Equation Models, Short Term Memory, Cognitive Processes, Cognitive Ability
Dinno, Alexis – Multivariate Behavioral Research, 2009
Horn's parallel analysis (PA) is the method of consensus in the literature on empirical methods for deciding how many components/factors to retain. Different authors have proposed various implementations of PA. Horn's seminal 1965 article, a 1996 article by Thompson and Daniel, and a 2004 article by Hayton, Allen, and Scarpello all make assertions…
Descriptors: Structural Equation Models, Item Response Theory, Computer Software, Surveys
Canetti-Nisim, Daphna; Halperin, Eran; Sharvit, Keren; Hobfoll, Stevan E. – Journal of Conflict Resolution, 2009
Does exposure to terrorism lead to hostility toward minorities? Drawing on theories from clinical and social psychology, we propose a stress-based model of political extremism in which psychological distress--which is largely overlooked in political scholarship--and threat perceptions mediate the relationship between exposure to terrorism and…
Descriptors: Jews, Intervals, Terrorism, Structural Equation Models
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