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SPR, Washington DC, May Trajectories of Smoking Among College Freshmen: Data from the UpTERN Study Brian R. Flay, Eisuke Segawa, Donald Hedeker, Craig Colder and TERN members

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SPR, Washington DC, May Selection of Subjects for These Analyses

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SPR, Washington DC, May Fitted Curve for Standard Mixed Effect Model

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SPR, Washington DC, May Statistical Model: Hybrid of HLM & GMM In pure GMM, classification is dominated by intercepts Our interest was more in changes over time, or slopes Therefore, we specified a common (random- effect) intercept model Model estimates only one intercept (mean over all subjects), but it provides intercept estimates for each subject as in HLM

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SPR, Washington DC, May

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7-class Common Random Intercept GMM

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SPR, Washington DC, May Class 1: Increasers

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SPR, Washington DC, May Class 2: Low-level increasers

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SPR, Washington DC, May Class 3: Occasional Smokers

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SPR, Washington DC, May Class 4: Regular Chippers

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SPR, Washington DC, May Class 5: Reducing Chippers

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SPR, Washington DC, May Class 6: Higher reducing chippers

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SPR, Washington DC, May Class 7: High variation decreasers

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SPR, Washington DC, May Classification by increase or decrease in smoking during the year

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SPR, Washington DC, May What happened to these groups the following year?

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SPR, Washington DC, May What happened to these groups the following year?

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SPR, Washington DC, May Conclusions The overall levels of smoking among college students are lower than expected Nevertheless, some students increased their rates of smoking and others decreased Hybrid HLM and Growth Mixture Analysis provided a meaningful grouping of students that described their patterns of smoking during freshman year All smokers are at risk of increasing or maintaining their smoking levels!

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