RESEARCH

The goal of my work is to investigate new and existing methods for the study of change in behavioral and social science. My research is focused at the intersection of theory and methods, my interest is in how to strike a balance to further our understanding of empirical data. Much of the work is concerned with longitudinal analysis and different approaches to modeling dynamic systems over time. This draws from a range of different disciplines including economics, computer science, mathematics, and control theory. The main goal is to approach questions from multiple angles and to readily integrate the useful tools developed in other disciplines into our own substantive work.

These goals and interests reflect a strong belief that, when empirical data is involved, no model is ever correct or true in the absolute sense. The most we can hope for is a close approximation of what we observe. In cases of simulated data, the investigation is primarily concerned with either verifying a methodological approach, or in qualitatively describing emergent behavior of systems.

TOPICS

Continuous Time Models

This area of research investigates psychological change by viewing time as continuous. This is accomplished through specifying models as systems of differential equations. Latent variable techniques, times series techniques, as well as state-space techniques are employed to understand the underlying mechanisms of change in continuous time. To the underlying process, as well, is the possible inclusion of stochastic input, thus turning these models from Ordinary Differential Equations, into Stochastic Differential Equations.

Exploratory and Nonlinear models of change over time.

In this area, atheoretic models of change are explored. Drawing on methods and approaches from other disciplines such as signal processing, computer vision, and machine learning, exploratory approaches to measurement and modeling are examined in order to gain insights about behavior and social interactions.

Statistical Computing

This area of research focuses on understanding the fundamental tools of statistical modeling including, global optimization, parameter estimation, data simulation, and data management. The emphasis is on computer programming to further our understanding of the behavior of particular techniques and approaches.