Jonathan J. Park

Jonathan J. Park

Position Title
Assistant Professor

Bio

About

Dr. Jonathan Park is an assistant professor of quantitative psychology in the Department of Psychology at UC Davis. I obtained my PhD in Human Development and Family Studies with a focus on Quantitative Methods from the Pennsylvania State University.

Formally, my research focuses on how to best handle and model heterogeneity in dynamic networks. People exhibit prototypical behavioral patterns that fluctuate over time, and individual dynamic networks tend to be largely idiosyncratic—very few people change and fluctuate in the same way. This makes identifying key dynamic patterns across individuals quite challenging.

For example, depression may manifest differently across individuals and their patterns of mood and behavior can vary significantly from person to person. By examining these dynamic patterns, we may uncover similarities in how depression unfolds across groups of people. However, different statistical models (e.g., multilevel, person-specific modeling) impose varying constraints on how individuals can differ relative to one another (e.g., continuous versus discrete differences) and whether we conclude whether individuals are similar at all.

My lab focuses on the impact of modeling decisions on the analysis of multi-subject multiple time-series and how these decisions can lead to dramatically different results such as the choice of modeling in discrete- or continuous-time. We also develop methods to reduce classification errors and ambiguity in group membership through the development and testing of community detection algorithms using principles of fuzzy statistics and distribution-based clustering methods.

Selected Publications

Park, J. J., Chow, S. M., Fisher, Z. F., & Molenaar, P. (2020). Affect and personality: Ramifications of modeling (non-) directionality in dynamic network models. European Journal of Psychological Assessment36(6), 1009.

Park, J. J., Fisher, Z. F., Chow, S. M., & Molenaar, P. C. (2023). Evaluating discrete time methods for subgrouping continuous processes. Multivariate Behavioral Research, 1-13.

Park, J. J., Chow, S. M., Epskamp, S., & Molenaar, P. C. (2024). Subgrouping with chain graphical var models. Multivariate behavioral research59(3), 543-565.