Dynamic Structural Equation Models

By T. Asparouhov, E. Hamaker, B. Muthén. 2018

796 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/fc0c0ec03fed479e08e05adfab0f1d29a1d916eb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Experimental and Cognitive Psychology

In Management Science and Operations Research

Citations in the corpus

The Gaussian Graphical Model in Cross-Sectional and Time-Series Data (2016, methodology): “Mplus allows for specifying random effects on the contemporaneous covariances and thus, by extension, allows for estimating random contemporaneous networks in addition to random temporal networks.”
Comparison of Models for the Analysis of Intensive Longitudinal Data (2019, methodology): “The new estimation of the RDSEM model is outlined in Appendix C in Asparouhov et al. (2018).”
On the Differences between General Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model: Interpretation of Cross-Lagged Parameters and Model Choice (2020, methodology): “, Asparouhov et al., 2018; Hamaker et al., 2015; Imai & Ratkovic, 2015; Robins, 1999; Robins & Hernán, 2009; Zyphur et al., 2020a). Among such methodologies, the general cross-lagged panel model (GCLM; Zyphur et al., 2020a, 2020b) is a recent variant of the CLPM. This model was not covered in the di”
Latent Variable Centering of Predictors and Mediators in Multilevel and Time-Series Models (2018, methodology): “The model is identical to the model given in equations (1-3).”
Number of Subjects and Time Points Needed for Multilevel Time-Series Analysis: A Simulation Study of Dynamic Structural Equation Modeling (2018, methodology): “This article aims to give insights and guidelines regarding the data requirements of some of the two-level timeseries models available in Mplus Version 8 (Muthén & Muthén, 2017) through the DSEM framework of Asparouhov et al. (2017b).”
Social Media Use and Adolescents’ Well-Being: Developing a Typology of Person-Specific Effect Patterns (2020, positive): “DSEM combines N = 1 time-series modeling, multilevel modeling, and structural equation modeling (Asparouhov et al., 2018; McNeish & Hamaker, 2020).”
Dynamic Latent Class Analysis (2017, background): “DSEMmodeling in Mplus is somewhat more general than what is described earlier; see Asparouhov et al. (2016).”