Methods and Measures: Growth mixture modeling: A method for identifying differences in longitudinal change among unobserved groups

Nilam Ram, Kevin J. Grimm

Research output: Contribution to journalReview article

346 Scopus citations

Abstract

Growth mixture modeling (GMM) is a method for identifying multiple unobserved sub-populations, describing longitudinal change within each unobserved sub-population, and examining differences in change among unobserved sub-populations. We provide a practical primer that may be useful for researchers beginning to incorporate GMM analysis into their research. We briefly review basic elements of the standard latent basis growth curve model, introduce GMM as an extension of multiple-group growth modeling, and describe a four-step approach to conducting a GMM analysis. Example data from a cortisol stress-response paradigm are used to illustrate the suggested procedures.

Original languageEnglish (US)
Pages (from-to)565-576
Number of pages12
JournalInternational Journal of Behavioral Development
Volume33
Issue number6
DOIs
StatePublished - Jan 1 2009

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All Science Journal Classification (ASJC) codes

  • Social Psychology
  • Education
  • Developmental and Educational Psychology
  • Social Sciences (miscellaneous)
  • Developmental Neuroscience
  • Life-span and Life-course Studies

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