The Impact of Ignoring a Level of Nesting Structure in Multilevel Growth Mixture Models: A Monte Carlo Study

By Qi Chen, Oi-man Kwok, Wen Luo, Victor L. Willson. 2010

60 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/74390872715354f56c6020355fbce33aeea15c80

How researchers see this paper

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

In Management Science and Operations Research

1. Wen Luo
2. Qi Chen

In Sociology and Political Science

1. Amber McEnturff
2. Wen Luo
3. Ryan Glaman
4. Gregory Palardy
5. Qi Chen

Citations in the corpus

• The Efficacy of Common Fit Indices for Enumerating Classes in Growth Mixture Models When Nested Data Structure Is Ignored (2017, methodology): “As shown in previous studies on multilevel analysis (e.g., Chen et al., 2010; Meyers & Beretvas, 2006; Moerbeek, 2004), ignoring the highest level data structure results in the redistribution of variance from the ignored level (i.e., the organization/school level) to the adjacent level (i.e., the…”