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1-112 - Continuous Time Dynamic Modeling

Thu, March 21, 2:15 to 3:45pm, Baltimore Convention Center, Floor: Level 3, Room 307

Session Type: Invited Address

Integrative Statement

The goal of this presentation is to introduce participants to continuous time dynamic modeling. Continuous time dynamic models are models for the analysis of change that make optimal use of the time structure to infer the development and dynamic relationships among constructs of interest. After distinguishing between static and dynamic models for the analysis of change and a short discussion of their respective advantages and disadvantages, I will introduce the basics of continuous time dynamic modeling in a stepwise fashion. I will highlight the possibility to work with intensive longitudinal data, including the analysis of N = 1 time-series (e.g., dynamic factor models), as well as panel data (T small, N large). Apart from a general introduction, special emphasis will be put on the interpretation and practical implementation of these models. I will end with an overview of recent developments, current limitations, and future research directions.

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Manuel Voelkle is professor for psychological research methods at the Humboldt University Berlin and an adjunct researcher at the Max Planck Institute for Human Development in Berlin, Germany. His research revolves around the development and application of new methods for the study of developmental dynamics in affective and cognitive functioning. Much of his recent work is concerned with continuous time modeling and the analysis of the intricate relationship of between- and within-person differences in psychological constructs as they evolve over time.