Student - College of Education

Cameron McCann is a doctoral student in the Quantitative Methods program in the Department of Educational Psychology. His research develops and evaluates statistical methods for causal inference in observational studies, with an emphasis on causal mediation analysis. This includes estimation of mediation effects in clustered data, causal inference with machine learning methods, sensitivity analysis methods, and uncertainty quantification.

Xiao Liu (Supervisor)
Statistical methods for causal mediation analysis, causal inference with machine learning methods, longitudinal or clustered data analysis, study design (e.g., statistical power analysis)

Liu, X. & McCann, C. (2026). Sensitivity analysis for unmeasured pretreatment confounders in causal mediation analysis with debiased machine learning. British Journal of Mathematical and Statistical Psychology. doi:10.1111/bmsp.70072.

McCann, C. & Liu, X. (2025). Evaluating Propensity Score Models for Estimating Causal Mediation Effects under Unmeasured Cluster-level Confounding. Health Services and Outcomes Research Methodology. https://link.springer.com/article/10.1007/s10742-025-00352-x#citeas. doi:https://doi.org/10.1007/s10742-025-00352-x.

Cameron M McCann