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Pascal Deboeck

Associate Professor
Quantitative Psychology

Ph.D., 2007, University of Notre Dame
Research Areas: Quantitative Psychology

pascal@ku.edu


Related Links
Quantitative Psychology Program
Personal Website

Research Interests

My research focuses on the development and application of derivatives, differential equation modeling, and dynamical systems concepts to intraindividual time series. The study of dynamical systems and the related topics of derivatives and differential equation modeling have a rich history of informing theories that address how, when and why variables change over time. These methods are conceptually ideal for psychology, particularly as questions about intraindividual change and variability are of growing interest. These methods may help address questions related to topics such as:

  1. the simultaneous coupling between variables,
  2. the relationship between change at different time scales,
  3. differences in intraindividual variability and
  4. the time scales at which intraindividual differences occur.

Unfortunately, the history of dynamical systems (and related methods) in the physical sciences has infrequently intersected with the statistical needs of the behavioral sciences, resulting in relatively few applications in the psychological literature. In developing new methods, I strive for tools that will allow a wider array of psychological data to be considered. This includes time series with relatively few observations, low sampling rates, large amounts of measurement and/or dynamic error, and unequally spaced or missing observations.

I try to integrate active methodological development with involved applied and methodological collaboration. My methodological research aims to improve derivative based analyses and methods for fitting differential equation models. My collaborative research allows me to benefit from the mutually informative interaction between theory and method, as well as combine other methodological areas with dynamical systems concepts.



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