Factors of Piecewise Growth Mixture Model: Distance and Pattern

2014 ◽  
Vol 46 (9) ◽  
pp. 1400 ◽  
Author(s):  
Yuan LIU ◽  
Fang LUO ◽  
Hongyun LIU
Keyword(s):  
Mixture Model ◽  
Growth Mixture Model ◽  
Growth Mixture

scholarly journals A parallel process growth mixture model of conduct problems and substance use with risky sexual behavior

2010 ◽  
Vol 111 (3) ◽  
pp. 207-214 ◽  
Author(s):  
Johnny Wu ◽  
Katie Witkiewitz ◽  
Robert J. McMahon ◽  
Kenneth A. Dodge
Keyword(s):  
Substance Use ◽  
Sexual Behavior ◽  
Conduct Problems ◽  
Mixture Model ◽  
Risky Sexual Behavior ◽  
Parallel Process ◽  
Growth Mixture Model ◽  
Growth Mixture

scholarly journals Does Money Matter? A Theory-Driven Growth Mixture Model to Explain Travel-Mode Choice with Experimental Data

Methodology ◽  
2006 ◽  
Vol 2 (3) ◽  
pp. 124-134 ◽  
Author(s):  
Eldad Davidov ◽  
Kajsa Yang-Hansen ◽  
Jan-Eric Gustafsson ◽  
Peter Schmidt ◽  
Sebastian Bamberg
Keyword(s):  
Mixture Model ◽  
Latent Class ◽  
Mode Choice ◽  
Growth Mixture Model ◽  
Travel Mode ◽  
High Importance ◽  
Growth Mixture ◽  
Travel Mode Choice ◽  
Changes Over Time ◽  
Over Time

In the present article we apply a growth mixture model using Mplus via STREAMS to delineate the mechanism underlying travel-mode choice. Three waves of an experimental field study conducted in Frankfurt Main, Germany, are applied for the statistical analysis. Five major questions are addressed: (1) whether the choice of public transport rather than the car changes over time; (2) whether a soft policy intervention to change travel mode choice has any effect on the travel-mode chosen; (3) whether one can identify different groups of people regarding the importance allocated to monetary and time considerations for the decision of which travel mode to use; (4) whether the different subgroups of people have different initial states and rates of change in their travel-model choices; (5) whether sociodemographic variables have an additional effect on the latent class variables and on the changes in travel-mode choice over time. We also found that choice of public transportation in our study is stable over time. Moreover, the intervention has an effect only on one of the classes. We identify four classes of individuals. One class allocates a low importance to both monetary and time considerations, the second allocates high importance to money and low importance to time, the third allocates high importance to both, and the fourth allocates a low importance to money and a high importance to time. We found no difference in the patterns of travel-mode changes over time in the four classes. We also found some additional effects of sociodemographic characteristics on the latent class variables and on behavior in the different classes. The model specification and the empirical findings are discussed in light of the theory of the allocation of time of Gary Becker.

Estimating a Conditional Growth Mixture Model (GMM)

2021 ◽  
pp. 191-213
Author(s):  
Kandauda A. S. Wickrama ◽  
Tae Kyoung Lee ◽  
Catherine Walker O'Neal ◽  
Frederick Lorenz
Keyword(s):  
Mixture Model ◽  
Growth Mixture Model ◽  
Growth Mixture

Psychopathology and resilience following traumatic injury: A latent growth mixture model analysis.

2010 ◽  
Vol 55 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Terri A. deRoon-Cassini ◽  
Anthony D. Mancini ◽  
Mark D. Rusch ◽  
George A. Bonanno
Keyword(s):  
Mixture Model ◽  
Traumatic Injury ◽  
Model Analysis ◽  
Latent Growth ◽  
Growth Mixture Model ◽  
Growth Mixture ◽  
Latent Growth Mixture Model

A Bayesian growth mixture model to examine maternal hypertension and birth outcomes

2011 ◽  
Vol 30 (22) ◽  
pp. 2721-2735 ◽  
Author(s):  
Brian Neelon ◽  
Geeta K. Swamy ◽  
Lane F. Burgette ◽  
Marie Lynn Miranda
Keyword(s):  
Mixture Model ◽  
Birth Outcomes ◽  
Growth Mixture Model ◽  
Growth Mixture ◽  
Maternal Hypertension
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