Literature DB >> 23885133

Growth Mixture Modeling: A Method for Identifying Differences in Longitudinal Change Among Unobserved Groups.

Nilam Ram1, Kevin J Grimm.   

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.

Entities:  

Year:  2009        PMID: 23885133      PMCID: PMC3718544          DOI: 10.1177/0165025409343765

Source DB:  PubMed          Journal:  Int J Behav Dev        ISSN: 0165-0254


  16 in total

Review 1.  The potential role of hypocortisolism in the pathophysiology of stress-related bodily disorders.

Authors:  C Heim; U Ehlert; D H Hellhammer
Journal:  Psychoneuroendocrinology       Date:  2000-01       Impact factor: 4.905

2.  Finite mixture modeling with mixture outcomes using the EM algorithm.

Authors:  B Muthén; K Shedden
Journal:  Biometrics       Date:  1999-06       Impact factor: 2.571

3.  Mixture or homogeneous? Comment on Bauer and Curran (2003).

Authors:  David Rindskopf
Journal:  Psychol Methods       Date:  2003-09

4.  Local solutions in the estimation of growth mixture models.

Authors:  John R Hipp; Daniel J Bauer
Journal:  Psychol Methods       Date:  2006-03

5.  If it goes up, must it come down? Chronic stress and the hypothalamic-pituitary-adrenocortical axis in humans.

Authors:  Gregory E Miller; Edith Chen; Eric S Zhou
Journal:  Psychol Bull       Date:  2007-01       Impact factor: 17.737

Review 6.  Latent variable modeling of differences and changes with longitudinal data.

Authors:  John J McArdle
Journal:  Annu Rev Psychol       Date:  2009       Impact factor: 24.137

7.  Latent growth curves within developmental structural equation models.

Authors:  J J McArdle; D Epstein
Journal:  Child Dev       Date:  1987-02

8.  Discrete-Time Survival Factor Mixture Analysis for Low-Frequency Recurrent Event Histories.

Authors:  Katherine E Masyn
Journal:  Res Hum Dev       Date:  2009

9.  Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes.

Authors:  B Muthén; L K Muthén
Journal:  Alcohol Clin Exp Res       Date:  2000-06       Impact factor: 3.455

10.  Self-esteem and neuroendocrine response to challenge: MacArthur studies of successful aging.

Authors:  T E Seeman; L F Berkman; B I Gulanski; R J Robbins; S L Greenspan; P A Charpentier; J W Rowe
Journal:  J Psychosom Res       Date:  1995-01       Impact factor: 3.006

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  238 in total

1.  Interventions to Reduce Spasticity and Improve Function in People With Chronic Incomplete Spinal Cord Injury: Distinctions Revealed by Different Analytical Methods.

Authors:  Lynsey D Duffell; Geoffrey L Brown; Mehdi M Mirbagheri
Journal:  Neurorehabil Neural Repair       Date:  2014-11-14       Impact factor: 3.919

2.  Individual differences in boys' and girls' timing and tempo of puberty: modeling development with nonlinear growth models.

Authors:  Kristine Marceau; Nilam Ram; Renate M Houts; Kevin J Grimm; Elizabeth J Susman
Journal:  Dev Psychol       Date:  2011-09

3.  Long-term course of ADHD symptoms from childhood to early adulthood in a community sample.

Authors:  Manfred Döpfner; Christopher Hautmann; Anja Görtz-Dorten; Fionna Klasen; Ulrike Ravens-Sieberer
Journal:  Eur Child Adolesc Psychiatry       Date:  2014-11-14       Impact factor: 4.785

4.  Poisson Growth Mixture Modeling of Intensive Longitudinal Data: An Application to Smoking Cessation Behavior.

Authors:  Mariya P Shiyko; Yuelin Li; David Rindskopf
Journal:  Struct Equ Modeling       Date:  2012-01       Impact factor: 6.125

5.  Assessing Community Readiness for Preventing Youth Substance Use in Colombia: A Latent Profile Analysis.

Authors:  Arthur de Oliveira Corrêa; Eric C Brown; Tae Kyoung Lee; Juliana Mejía-Trujillo; Augusto Peréz-Gómez; Nicole Eisenberg
Journal:  Int J Ment Health Addict       Date:  2020-01-02       Impact factor: 3.836

6.  Trajectories of maltreatment re-reports from ages 4 to 12:: evidence for persistent risk after early exposure.

Authors:  Laura J Proctor; Gregory A Aarons; Howard Dubowitz; Diana J English; Terri Lewis; Richard Thompson; Jon M Hussey; Alan J Litrownik; Scott C Roesch
Journal:  Child Maltreat       Date:  2012-06-20

7.  Individual and Social Factors Related to Trajectories of Blackouts among Underage Drinkers in the Emergency Department.

Authors:  Erin E Bonar; Jason E Goldstick; Rebecca M Cunningham; Anne C Fernandez; Alan K Davis; Mark A Ilgen; Maureen A Walton
Journal:  Alcohol Alcohol       Date:  2019-07-01       Impact factor: 2.826

8.  Differential Growth Trajectories for Achievement Among Children Retained in First Grade: A Growth Mixture Model.

Authors:  Qi Chen; Jan N Hughes; Oi-Man Kwok
Journal:  Elem Sch J       Date:  2014-03

9.  Quality of life trajectories after diagnosis of gynecologic cancer: a theoretically based approach.

Authors:  Brian D Gonzalez; Sharon L Manne; Jerod Stapleton; Shannon Myers-Virtue; Melissa Ozga; David Kissane; Carolyn Heckman; Mark Morgan
Journal:  Support Care Cancer       Date:  2016-10-19       Impact factor: 3.603

10.  Trajectories of Alcohol Initiation and Use During Adolescence: The Role of Stress and Amygdala Reactivity.

Authors:  Nourhan M Elsayed; M Justin Kim; Kristina M Fields; Rene L Olvera; Ahmad R Hariri; Douglas E Williamson
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2018-06-18       Impact factor: 8.829

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