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Model Fit and Comparison in Finite Mixture Models: A Review and a Novel Approach

Frontiers in Education, 2021
One of the greatest challenges in the application of finite mixture models is model comparison. A variety of statistical fit indices exist, including information criteria, approximate likelihood ratio tests, and resampling techniques; however, none of ...
Kevin J. Grimm, Russell Houpt, Danielle Rodgers   +2 more
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An Introduction to Latent Variable Mixture Modeling (Part 2): Longitudinal Latent Class Growth Analysis and Growth Mixture Models [PDF]

Journal of Pediatric Psychology, 2013
Pediatric psychologists are often interested in finding patterns in heterogeneous longitudinal data. Latent variable mixture modeling is an emerging statistical approach that models such heterogeneity by classifying individuals into unobserved groupings (latent classes) with similar (more homogenous) patterns.
Berlin, Kristoffer S., Parra, Gilbert R., Williams, Natalie A.   +2 more
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Growth trajectories in lipid profile and fasting blood sugar in prediabetic people over a 16- year follow-up and future risk of type2 diabetes mellitus: A latent growth modeling approach

Alexandria Journal of Medicine, 2022
Introduction The current study aimed to investigate whether the pattern of changes in lipid profile and fasting blood sugar (FBS) can predict the future risk of type 2 diabetes mellitus (T2DM) incidence in prediabetic people.Methods In a prospective ...
Awat Feizi, Fahimeh Haghighatdoost, Parisa Zakeri, Ashraf Aminorroaya, Masoud Amini   +4 more
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Patterns of adverse childhood experiences and depressive symptom trajectories in young adults: A longitudinal study of college students in China

Frontiers in Psychiatry, 2022
BackgroundAdverse childhood experiences (ACEs) tend to cluster together in daily life, and most studies focus on the level of depression at certain points, but the dynamic process of depression is often neglected.
Shuqin Li, Shuqin Li, Rui Wang, Erica Thomas, Zhicheng Jiang, Zhicheng Jiang, Zhengge Jin, Zhengge Jin, Ruoyu Li, Ruoyu Li, Yan Qian, Xianbing Song, Ying Sun, Ying Sun, Shichen Zhang, Shichen Zhang, Ruoling Chen, Yuhui Wan, Yuhui Wan   +18 more
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Extracting Spurious Latent Classes in Growth Mixture Modeling With Nonnormal Errors [PDF]

Educational and Psychological Measurement, 2016
Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests.
Kiero, Guerra-Peña, Douglas, Steinley
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BMI Trajectories During the First 2 Years, and Their Associations With Infant Overweight/Obesity: A Registered Based Cohort Study in Taizhou, China

Frontiers in Pediatrics, 2021
Objective: The purpose of this study was to identify trajectories of body mass index (BMI) in toddlers from birth to 2 years old and examine their association with infantile overweight/obesity.Methods: Data were collected from 19,054 children born in any
Tian Zhang, Ying Song, Haoyue Teng, Yue Zhang, Jianan Lu, Linghua Tao, Yanjie Jin, Yanjie Jin, Jieyun Yin, Danhong Zhou   +9 more
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School climate and bullying victimization: A latent class growth model analysis. [PDF]

School Psychology Quarterly, 2014
Researchers investigating school-level approaches for bullying prevention are beginning to discuss and target school climate as a construct that (a) may predict prevalence and (b) be an avenue for school-wide intervention efforts (i.e., increasing positive school climate).
Nicholas A, Gage, Debra A, Prykanowski, Alvin, Larson   +2 more
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Bayesian Inference for Growth Mixture Models with Latent Class Dependent Missing Data [PDF]

Multivariate Behavioral Research, 2011
Growth mixture models (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data.
Zhenqiu Laura, Lu, Zhiyong, Zhang, Gitta, Lubke   +2 more
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Exploring Class Enumeration in Bayesian Growth Mixture Modeling Based on Conditional Medians

Frontiers in Education, 2021
Growth mixture modeling is a popular analytic tool for longitudinal data analysis. It detects latent groups based on the shapes of growth trajectories.
Seohyun Kim, Xin Tong, Zijun Ke
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Latent class growth modelling for the evaluation of intervention outcomes: example from a physical activity intervention [PDF]

Journal of Behavioral Medicine, 2021
AbstractIntervention studies often assume that changes in an outcome are homogenous across the population, however this assumption might not always hold. This article describes how latent class growth modelling (LCGM) can be performed in intervention studies, using an empirical example, and discusses the challenges and potential implications of this ...
Anna-Maria Lampousi, Jette Möller, Yajun Liang, Daniel Berglind, Yvonne Forsell   +4 more
openaire   +2 more sources