February 13, 2024Multivariate Behavioral ResearchOpen Access

Subgrouping with Chain Graphical VAR Models

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Authors

JPJonathan Park SCSy‐Miin Chow SESacha Epskamp

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Overview

Simulation study demonstrates subgrouping accuracy in chain graphical vector autoregression, highlighting improved detection of subtle contemporaneous dynamic differences.

Key Points

The subgrouped chain graphical vector autoregression identifies shared dynamic network structures in both lag(1) and contemporaneous effects across distinct participant subgroups.
Monte Carlo simulations demonstrate that the model achieves heightened sensitivity for detecting nuanced group differences while simultaneously keeping Type-I error rates low.
Alternating least squares VAR effectively identifies groups separated by larger distances, highlighting distinct strengths and practical trade-offs between both network estimation methods.

Cite This Study

Park et al. (2024) studied this question.

synapsesocial.com/papers/68e7956cb6db643587705d93 https://doi.org/10.1080/00273171.2023.2289058

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February 13, 2024Multivariate Behavioral ResearchOpen Access

Subgrouping with Chain Graphical VAR Models

View Full Paper

Ask AI

Bookmark

Authors

JPJonathan Park SCSy‐Miin Chow SESacha Epskamp

Discussion

Member takes

Overview

Simulation study demonstrates subgrouping accuracy in chain graphical vector autoregression, highlighting improved detection of subtle contemporaneous dynamic differences.

Key Points

The subgrouped chain graphical vector autoregression identifies shared dynamic network structures in both lag(1) and contemporaneous effects across distinct participant subgroups.
Monte Carlo simulations demonstrate that the model achieves heightened sensitivity for detecting nuanced group differences while simultaneously keeping Type-I error rates low.
Alternating least squares VAR effectively identifies groups separated by larger distances, highlighting distinct strengths and practical trade-offs between both network estimation methods.

Cite This Study

Park et al. (2024) studied this question.

synapsesocial.com/papers/68e7956cb6db643587705d93 https://doi.org/10.1080/00273171.2023.2289058

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