DETECTING DIFFERENTIAL EFFECTS USING REGRESSION MIXTURE MODELS: Applications Using Mplus

Minjung Kim, Junyeong Yang

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Culturally responsive methods have been mostly developed under the qualitative research methodology framework since quantitative methods tend to totalize and homogenize different population groups based on the majority group. When quantitative methods are used, regression analysis with interaction (or moderation) effects is one way to better understand the heterogeneity in the effects of predictors on an outcome. In this chapter, Kim and Yang describe the regression interaction approach with an example context of perceived discrimination and antisocial behavior. Next, they introduce another quantitative method, the regression mixture modeling, to explore the potential heterogeneity in the effects of predictors on an outcome in regression analysis. The authors also provide the step-by-step tutorial for analyzing the regression mixture models with an example data using a statistical software, Mplus 8.

Original languageEnglish
Title of host publicationAdvancing Culturally Responsive Research and Researchers
Subtitle of host publicationQualitative, Quantitative, and Mixed Methods
PublisherTaylor and Francis
Pages181-200
Number of pages20
ISBN (Electronic)9781000640892
ISBN (Print)9780367648596
DOIs
Publication statusPublished - 1 Jan 2022

Bibliographical note

Publisher Copyright:
© 2023 selection and editorial matter, Penny A. Pasque and e alexander individual chapters, the contributors.

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