APS
2022 APS Annual Convention · 2022
Performance of Bayesian Model Fit Indices for Knot Specification in Piecewise Growth Curve Modeling
- Lydia Marvin
University of California, Merced - Haiyan Liu
University of California, Merced - Sarah Depaoli
University of California, Merced
Abstract
Bayesian piecewise linear growth modeling is a flexible tool for capturing nonlinear change. It breaks the overall growth trajectory into connected linear segments. In this study, we evaluated Bayesian model indices for specifying changepoints. Our results suggest the BIC and DIC have decent selection rates for the true model.
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