One of my research themes is understanding sources of unwanted variation, from noncompliance to confounding. Some of my areas of focus include:
- causal inference
- experimental controls, negative and positive controls
- Bayesian modeling
- experimental design
Publications and Working Papers
L. Campos, M. Glickman, K. Hunter. Measuring effects of medication adherence on near-term time-varying health outcomes using marginal Bayesian dynamic linear models. Biostatistics, 2020
K. Hunter, M. Glickman, L. Campos. Inferring medication adherence from time-varying health measures. Submitted. arXiv:2104.11651
K. Hunter, K. Koenig, M.A. Bind. Conceptualizing experimental controls using the potential outcomes framework. Manuscript in preparation. arXiv:2104.10302
N. Pashley, K. Hunter, K. McKeough, T. Dasgupta, D. Rubin. Causal inference from treatment- control studies having a pseudo-factor with unknown assignment mechanism. Submitted.
D. Hsu, K. Hunter, G. Cartwright, L. Garcia, M. Li, K. Shaw, M. Sutton, Y. Yin. Relative influences on regulator approval of energy utility rates. Submitted.
K. Hunter, J. Gagnon-Bartsch. Confounding and population stratification in genetics studies. Work in progress.
K. Porter, L. Matrix, K. Hunter. Estimating statistical power in multi-level experimental designs when using multiple testing procedures. Work in progress.
K. Hunter, J. Gagnon-Bartsch, T. Speed. Using estimated negative controls to improve inference in genetics experiments. Work in progress.
- Marie-Abele Bind, Massachusetts General Hospital
- Luis Campos, Etsy, Inc.
- Tirthankar Dasgupta, Rutgers University
- Johann Gagnon-Bartsch, University of Michigan
- Mark Glickman, Harvard University
- David Hsu, MIT
- Katy McKeough, Red Sox
- Luke Miratrix, Harvard University
- Nicole Pashley, Rutgers University
- Kristin Porter, MDRC
- Donald Rubin, Tsinghua University and Temple University
- Terry Speed, Walter and Eliza Hall Institute of Medical Research