Chelsea Muth

Graduate Student Researcher

I am a quantitative psychology doctoral student. Broadly, my work centers on psychological health and what shapes our human processes -- e.g., emotion, cognition, perception, learning, social interaction, physiology -- over time. My current research focuses on measures of emotion and psychological well-being, studied across repeated occasions, over varying time scales. More specifically, I work in Dr. Zita Oravecz's lab on longitudinal modeling in the Bayesian statistical framework for social science applications. My research focuses on assessing individual development by modeling within-person variation and change (growth curves, time series, dynamic process models, nonlinear models), describing within-person variability with person-specific parameters, and comparing across individuals with both person-specific and population-level parameters. In the Bayesian framework, I focus on estimation with precision and measurement with uncertainty via the posterior distribution. I am interested in applying Bayesian methods to social science research, and also in teaching and publishing on the advantages of such applications. I strive to present Bayesian methods with graphics and tutorials that are approachable for non-methodological audiences. To achieve this goal, I continue to draw on my background in journalism, communications, and teaching.

Projects Joined

Publications

Oravecz, Z., Muth, C., & Vandekerckhove, J.. (2016). Do People Agree on What Makes One Feel Loved? A Cognitive Psychometric Approach to the Consensus on Felt Love. (X. Weng, Ed.)PLOS ONE, 11(4), e0152803. presented at the Jan-04-2016. doi:10.1371/journal.pone.0152803