Original paper
Growth mixture modeling with non‐normal distributions
Abstract
A limiting feature of previous work on growth mixture modeling is the assumption of normally distributed variables within each latent class. With strongly non‐normal outcomes, this means that several latent classes are required to capture the observed variable distributions. Being able to relax the assumption of within‐class normality has the advantage that a non‐normal observed distribution does not necessitate using more than one class to fit...
Paper Details
Title
Growth mixture modeling with non‐normal distributions
Published Date
Dec 11, 2014
Journal
Volume
34
Issue
6
Pages
1041 - 1058
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History