Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study

dc.contributor.authorKim, Minjung
dc.contributor.authorLamont, Andrea E.
dc.contributor.authorJaki, Thomas
dc.contributor.authorFeaster, Daniel
dc.contributor.authorHowe, George
dc.contributor.authorVan Horn, M. Lee
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.contributor.otherUniversity of South Carolina Columbia
dc.contributor.otherLancaster University
dc.contributor.otherUniversity of Miami
dc.contributor.otherGeorge Washington University
dc.contributor.otherUniversity of New Mexico
dc.date.accessioned2023-09-28T19:38:48Z
dc.date.available2023-09-28T19:38:48Z
dc.date.issued2016
dc.description.abstractRegression mixture models are a novel approach to modeling the heterogeneous effects of predictors on an outcome. In the model-building process, often residual variances are disregarded and simplifying assumptions are made without thorough examination of the consequences. In this simulation study, we investigated the impact of an equality constraint on the residual variances across latent classes. We examined the consequences of constraining the residual variances on class enumeration (finding the true number of latent classes) and on the parameter estimates, under a number of different simulation conditions meant to reflect the types of heterogeneity likely to exist in applied analyses. The results showed that bias in class enumeration increased as the difference in residual variances between the classes increased. Also, an inappropriate equality constraint on the residual variances greatly impacted on the estimated class sizes and showed the potential to greatly affect the parameter estimates in each class. These results suggest that it is important to make assumptions about residual variances with care and to carefully report what assumptions are made.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.citationKim, M., Lamont, A. E., Jaki, T., Feaster, D., Howe, G., & Van Horn, M. L. (2015). Impact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation study. In Behavior Research Methods (Vol. 48, Issue 2, pp. 813–826). Springer Science and Business Media LLC. https://doi.org/10.3758/s13428-015-0618-8
dc.identifier.doi10.3758/s13428-015-0618-8
dc.identifier.orcidhttps://orcid.org/0000-0003-1297-098X
dc.identifier.orcidhttps://orcid.org/0000-0002-1096-188X
dc.identifier.urihttps://ir.ua.edu/handle/123456789/11668
dc.languageEnglish
dc.language.isoen_US
dc.publisherSpringer
dc.subjectRegression mixture
dc.subjectDifferential effects
dc.subjectEffect heterogeneity
dc.subjectResidual variances
dc.subjectMODELS
dc.subjectPREDICTORS
dc.subjectPATTERNS
dc.subjectFAMILY
dc.subjectPsychology, Mathematical
dc.subjectPsychology, Experimental
dc.titleImpact of an equality constraint on the class-specific residual variances in regression mixtures: A Monte Carlo simulation studyen_US
dc.typeArticle
dc.typetext
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