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A primer on two-level dynamic structural equation models for intensive longitudinal data in Mplus.

Bibliographic Data

ID23328007
AuthorsDaniel McNeish (0000-0003-1643-9408, Arizona State University), Ellen L Hamaker (Utrecht University)
Year2020
Volume25
Issue5
Pages610-635
Publication date2020-10-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenuePsychological Methods (JOURNAL)
Journal identifiersISSN: 1082-989X • E-ISSN: 1939-1463
PublisherAmerican Psychological Association (APA) (PUBLISHER)
DOI10.1037/met0000250
PMID31855015
OpenAlexW2930003956
LanguageEN
Citations received170
References cited41

Version 8. The goal is to provide readers with a basic conceptual understanding of common models, template code, and result interpretation. We provide short descriptions of some advanced issues, but our main priority is to supply readers with a solid knowledge base so that the more advanced literature on the topic is more readily digestible to a larger group of researchers. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Data mining · Econometrics · Longitudinal data · Physics · Primer (cosmetics) · Statistics · Structural equation modeling · Computer Science · Functional Brain Connectivity Studies · Heart Rate Variability and Autonomic Control · Mathematics · Mental Health Research Topics · Psychology

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Unique citing works170
Citations per year28,33
Citation span2020 - 2026 (7)
Citation velocitycurrent
Highly citedYes
Citation typesNeutral: 159

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