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Graduate Seminar; Multilevel Modeling

Students are provided with an introduction to multilevel modeling techniques (also termed "hierarchical linear models," "mixed effects models," and "random coefficient models"), with an emphasis on applications. Specific topics that are covered include conceptualization and specification of multilevel models, interpretation of parameter estimates, and application in computer programs using existing datasets. Applications will include a) individuals nested within groups; b) repeated measures/idiographic analysis; c) dyadic studies; d) daily-diary studies; and e) growth-curve modeling. Readings and examples will be drawn from clinical psychology, cognitive psychology, developmental psychology, educational psychology, and social psychology. Students are encouraged to use their own research data for course assignments

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Average GPA: 3.67 between 29 students

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