Caleb Miles, PhD

  • Assistant Professor, Biostatistics
212-305-1696

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Overview

Caleb Miles: Two fundamental problems in causal mediation analysis

Dr. Caleb Miles works on developing semiparametric methods for causal inference and applying them to problems in public health. His applied work is largely in HIV/AIDS, psychiatry, anesthesiology, and drug abuse. His methodological research interests include causal inference, its intersection with machine learning, mediation analysis, transportability/generalizability, and measurement error.

Academic Appointments

  • Assistant Professor, Biostatistics

Credentials & Experience

Education & Training

  • BS, 2009 Mathematics, University of Alabama
  • PhD, 2015 Biostatistics, Harvard University

Committees, Societies, Councils

  • 2023 – Present: Associate Editor, Journal of the Royal Statistical Society, Series C
  • 2018 – Present: Associate Editor, International Journal of Biostatistics 

Honors & Awards

  • 2023: Departmental grant writing initiative, Department of Biostatistics, Columbia Mailman School of Public Health
  • 2022: Calderone Junior Faculty Award, Columbia Mailman School of Public Health 

Research

Research Interests

  • Biostatistical Methods
  • Causal Inference
  • Drug abuse and dependence
  • HIV/AIDS
  • Machine learning and artificial intelligence
  • Measurement Error
  • Mediation Analysis
  • Mental Health
  • Semiparametric Inference
  • Sensitivity Analysis
  • Transportability and Generalizability

Grants

Past Grants

TRANSFORM KL2 Mentored Career Development Award, Irving Institute for Clinical and Translational Research
Personalizing Treatment Decisions and Understanding Causal Mechanisms for Functional and Occupational Outcomes Among Patients With Schizophrenia
2020–2023

Selected Publications

Miles, C.H. “On the causal interpretation of randomised interventional indirect effects.” Journal of the Royal Statistical Society Series B: Statistical Methodology, 2023: qkad066, https://doi.org/10.1093/jrsssb/qkad066

Miles, C.H., Shpitser, I., Kanki, P., Meloni, S., & Tchetgen Tchetgen, E.J. "On semiparametric estimation of a path-specific effect in the presence of mediator-outcome confounding." Biometrika: 107(1). 159-172, 2020. https://pubmed.ncbi.nlm.nih.gov/33390591/

Miles, C.H., Petersen, M., & van der Laan, M.J. "Causal inference when counterfactuals depend on the proportion of all subjects exposed." Biometrics: 75(3). 768-777, 2019. https://pubmed.ncbi.nlm.nih.gov/30714118/

Miles, C.H., Schwartz, J., & Tchetgen Tchetgen, E.J. "A class of semiparametric tests of treatment effect robust to confounder measurement error." Statistics in Medicine: 37(24). 3403-3416, 2018. https://pubmed.ncbi.nlm.nih.gov/29938816/

Miles, C.H., Shpitser, I., Kanki, P., Meloni, S., & Tchetgen Tchetgen, E.J. "Quantifying an adherence path-specific effect of antiretroviral therapy in the Nigeria PEPFAR program." Journal of the American Statistical Association: 112(520). 1443-1452, 2017. https://pubmed.ncbi.nlm.nih.gov/32042214/

Miles, C.H., Kanki, P., Meloni, S., & Tchetgen Tchetgen, E.J. "On partial identification of the natural indirect effect." Journal of Causal Inference: 5(2). 2017. https://www.degruyter.com/document/doi/10.1515/jci-2016-0004/html