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| PSY 61101 - Multilevel Theory, Measurement And Analysis |
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Credit Hours: 3.00. This course is designed to provide doctoral students with an introductory treatment of multilevel theory building and testing. Issues to be discussed include: multilevel theory building, composition and compilation models, aggregation, aggregation bias, the role of within-group agreement in multilevel modeling, cross-level inference, cross-level interactions, and hierarchical linear modeling. Permission of instructor required. Typically offered Fall Spring.
3.000 Credit hours Syllabus Available Levels: Undergraduate, Graduate, Professional Schedule Types: Lecture Offered By: College of Health & Human Sci Department: Psychological Sciences May be offered at any of the following campuses: West Lafayette Learning Outcomes: 1. Acquire an understanding of the basic elements of multilevel theories and multilevel validation and how those theories and validation processes differ from single-level theories/processes. 2. Acquire an understanding of the roles of data aggregation & cross-level inference in multilevel measurement and analysis. 3. Acquire an understanding of the various ways to estimate interrater agreement & reliability and how those statistics are used to inform multilevel measurement. 4. Acquire an understanding of the hierarchical linear model applied to traditional nested data structures. Emphasis will be placed on model specification and interpretation of parameter estimates. 5. Acquire an understanding of the hierarchical linear model applied to longitudinal data structures. Emphasis will be placed on model specification and interpretation of parameter estimates. 6. Acquire an understanding of various "special topics" in multilevel theory, measurement, and analysis. Examples include: multilevel mediation, multilevel moderation, multilevel analysis of dyadic data, and the impact of centering decisions on the interpretation of multilevel models. Restrictions: Must be enrolled in one of the following Levels: Graduate |
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