An introduction to latent class growth analysis and growth mixture modeling.

By Tony Jung, K. A. S. Wickrama. 2008

3,092 citations recorded by the source corpus.

Subfields: Management, Monitoring, Policy and Law, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/c94cf3f9b2580a1249586aa3fe6e4f3f5a5736f1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management, Monitoring, Policy and Law

1. K. Jung
2. R. Sprott
3. S. Anderson
4. A. Mancini
5. M. Syed
6. Ulla Kinnunen *
7. Paul J Silvia
8. Alex J. Bowers

In Sociology and Political Science

1. T. Kashdan
2. Paul J Silvia
3. V. Dupéré
4. G. Bonanno
5. Patrick Gaudreau
6. S. Anderson
7. K. Jung
8. R. Sprott

Citations in the corpus

• The Relationship Between Teachers’ Implementation of Classroom Management Practices and Student Behavior in Elementary School (2018, background): “Entropy is an index bound between 0 and 1 that assesses the precision of latent class membership, with higher precision of classification for values closer to 1 (Jung & Wickrama, 2008).”
• Interesting things and curious people: Exploration and engagement as transient states and enduring strengths. (2009, methodology): “The field of statistical classification is vast, but a convenient method for our data is to apply a latent class extension of a conventional multilevel model, known as semi-parametric group-based models, latent class growth models, and growth mixture models (Jung & Wickrama, 2008; Nagin, 1999).”
• Beyond Resilience and PTSD: Mapping the Heterogeneity of Responses to Potential Trauma (2012, methodology): “…contrast to traditional assumptions of homogeneity, recent conceptual (Bonanno, 2004; Mancini, Bonanno, & Clark, 2009) and statistical (Curran & Hussong, 2003; Jung & Wickrama, 2008; Muthén & Muthén, 2004) advances have dramatically underscored the natural heterogeneity of human stress responding.”
• Why Tenth Graders Fail to Finish High School: A Dropout Typology Latent Class Analysis (2012, methodology): “Following the recommendations of the mixture modeling literature (Jung & Wickrama, 2008; Lo, 2005; Lo, Mendell, & Rubin, 2001), and given the ambiguity of the number of dropout categories in the dropout typology literature that hypothesized multiple overlapping dropout types, we tested an iterative…”
• Weighing the Costs of Disaster (2010, background): “However, both conceptual (Bonanno, 2004, 2005; Bonanno & Mancini, 2008, in press) and statistical (Curran & Hussong, 2003; Jung & Wickrama, 2008; Muthen, 2004) perspectives on reactivity to life stress suggest a dramatically different picture—one that emphasizes the natural heterogeneity of…”
• Modeling recovery curves with application to prostatectomy. (2015, neutral): “Functional data analysis (Ramsay and Silverman, 2002; Denison and others, 1998) and growth curve modeling (Jung and Wickrama, 2008) are rich areas of past study, but existing models from those fields do not guarantee that the predicted time series possesses a recovery curve shape, that it drops foll”
• A review of 25 years of research in bidirectionality in parent–child relationships (2016, methodology): “Growth mixture models identify latent classes that represent different patterns of growth, so as to identify interindividual and intraindividual stability change as well as the predictors of each type with greater emphasis on developmental processes (Jung & Wickrama, 2008).”
• Using Group-Based Trajectory and Growth Mixture Modeling to Identify Classes of Change Trajectories (2016, methodology): “The BLRT has been recommended as a better fit statistic than the BIC (Jung & Wickrama, 2008; Nylund et al., 2007).”