The Efficacy of Common Fit Indices for Enumerating Classes in Growth Mixture Models When Nested Data Structure is Ignored: A Monte Carlo Study (open access)

The Efficacy of Common Fit Indices for Enumerating Classes in Growth Mixture Models When Nested Data Structure is Ignored: A Monte Carlo Study

This article investigates whether the correct number of classes can still be retrieved when a higher level of nesting in multilevel growth mixture model (MGMM) is ignored.
Date: March 30, 2017
Creator: Chen, Qi; Luo, Wen; Palardy, Gregory J.; Glaman, Ryan & McEnturff, Amber
System: The UNT Digital Library