Ken Bollen: Causal inference with random assignment vs. researcher created binary treatments

Ken Bollen will present “Causal inference with random assignment vs. researcher created binary treatments” as part of the Carolina Population Center’s 2023-2024 Interdisciplinary Research Seminar Series.

Ken Bollen develops new quantitative methods to apply to the population and social/behavioral sciences. These include new models to analyze longitudinal data, creative approaches to analyzing difficult-to-measure concepts, and developing estimators that have greater robustness to the approximate nature of our models. He also is working on comparing and integrating different approaches to causal inference. Population studies, health, and trauma are the contexts within which he develops these methods while also addressing practical substantive questions.

Ken Bollen’s research focuses on creating new statistical tools that have applications across a wide range of population areas. Many of these tools are developed within the field of latent variable structural equation models (SEMs). SEMs formulate systems of equations, allow multiple “dependent” variables with mediation effects, and take account of the measurement error commonly found in population-related variables. Collaborating with a number of CPC fellows, postdocs, and graduate trainees, Bollen has applied SEMs to topics such as evaluating the use of birth weight, gestational age, and birth length as measures of a mother’s fetal conditions, assessing the measurement properties of self-rated health and depression measures, evaluating the quality of physiological measures from surveys, and analyzing the effects of SES on fertility. Many of these projects have utilized CPC-based data such as those from Add Health and the Cebu Longitudinal Health and Nutrition Survey.