Covariates and Mixture Modeling: Results of a Simulation Study Exploring the Impact of Misspecified Effects on Class Enumeration

By Karen Nylund-Gibson, Katherine E. Masyn. 2016

266 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/490bf28b65cd388be5029694368262958ec44c3b

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Citations in the corpus

Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers (2020, methodology): “When to include covariates has been debated within the LPA/ LCA literature; simulation studies have supported the preference for including covariates after the original model retention decision is made (Nylund-Gibson & Masyn, 2016).”
Prediction from Latent Classes: A Demonstration of Different Approaches to Include Distal Outcomes in Mixture Models (2019, methodology): “A recent simulation study by Nylund-Gibson and Masyn (2016), using latent class analysis, focused on understanding the impact of covariate effect misspecification on the class enumeration process.”
Person-Centered Methodologies in the Organizational Sciences (2018, background): “Despite the fact that recent statistical research (Diallo, Morin, & Lu, 2017; Nylund-Gibson & Masyn, 2016) has shown that covariates (predictors, outcomes, or correlates) need to be integrated to a person-centered solution once the most optimal unconditional model (without covariates) has been…”
Latent Class Analysis: A Guide to Best Practice (2020, methodology): “Because nuances of including covariates in LCA models vary by statistical software and the approaches used, researchers are encouraged to consult articles with details on the topic (e.g., Asparouhov & Muthén 2014; Nylund-Gibson & Choi, 2018; Nylund-Gibson & Masyn, 2016; Vermunt & Magidson, 2016).”
Measurement Invariance and Differential Item Functioning in Latent Class Analysis With Stepwise Multiple Indicator Multiple Cause Modeling (2017, background): “However, as shown most recently by Nylund-Gibson and Masyn (2016), if the conditional latent class model with predictors is misspecified, the class enumeration process can be distorted.”