INSERM Workshop, St. RaphaelMixture modeling for

longitudinal dataIntroduction

Bruno FalissardUniv. Paris-Sud, INSERM U669

Mixture modeling for longitudinal data

• Everybody says that longitudinal data are essential

• Most often– T1, T2, T3, T4– T4 explained by T1

• Another perspective : typical patterns of evolution across time

Mixture modeling for longitudinal dataTe

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People with fever receiving an antibiotic

Mixture modeling for longitudinal dataTe

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People with fever receiving an antibiotic

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Mixture modeling for longitudinal dataTe

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People with fever receiving an antibiotic

Mixture modeling for longitudinal dataTe

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Virus

Bacteria

People with fever receiving an antibiotic

• good or bad responders in RCTs• developmental perspective• …

Mixture modeling for longitudinal data

• Why this workshop today and not several years ago?– The questions did exist several years ago– But• Somewhat exploratory approach (not classical in

biomedical research)• Tools more or less efficient (big sample sizes,

transversal data)

Mixture modeling for longitudinal data

• But the first applications appeared…– Trajectory of aggression in young children

• With user-friendly routines• With some elements of robustness

Mixture modeling for longitudinal data

• These models are somewhat different from the classical techniques used in biomedical research– “Bottom up” as opposed to “top down”– Intersection of numerous methodological fields• Biostatistics• Computer science• Social sciences• Psychometrics

Mixture modeling for longitudinal data

• Statistics are not only mathematics, statistics are highly dependant on the background of application (culture)– Unique opportunity to confront different type of

approaches– With statistical and practical considerations– With the objective to be confident with these

methods, and to be able to explain them to reviewers

Mixture modeling for longitudinal data