Linda Valeri, PhD

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Overview

Linda Valeri is an assistant professor in Biostatistics at the Columbia University Mailman School of Public Health. Dr. Valeri joined the Department of Biostatistics at Columbia University in 2018 after 3 years as faculty at the Laboratory of Psychiatric Biostatistics of McLean Hospital and the Department of Psychiatry at Harvard Medical School. Dr. Valeri received her PhD in Biostatistics from Harvard University in 2013, where her dissertation focused on statistical methods for causal mediation analysis. Dr. Valeri is an expert in causal inference with a focus on statistical methods for causal mediation analysis, measurement error, and missing data. She is interested in translating statistical methods in public health to improve our understanding of mental health, environmental determinants of health, and health disparities.

Academic Appointments

  • Assistant Professor of Biostatistics

Credentials & Experience

Education & Training

  • BA, 2006 Bocconi University, Milan, Italy
  • MSc, 2008 Bocconi University, Milan, Italy
  • MA, 2010 Harvard University, Cambridge, MA
  • PhD, 2013 Harvard University, Cambridge, MA

Committees, Societies, Councils

Adjunct Assistant Professor, Department of Epidemiology, Harvard T.H. Chan School of Public Health

Research

Research Interests

  • Biostatistical Methods
  • Community Health
  • Environmental Health
  • Mental health

Selected Publications

Valeri, L., Reese, S. L., Zhao, S., Page, C. M., Nystad, W., Coull, B. A., & London, S. J. (2017). Misclassified exposure in epigenetic mediation analyses. Does DNA methylation mediate effects of smoking on birthweight?. Epigenomics, 9(3), 253-265.

Valeri, L., & VanderWeele, T. J. (2013). Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros. Psychological methods, 18(2), 137.

Valeri, L., Lin, X., & VanderWeele, T. J. (2014). Mediation analysis when a continuous mediator is measured with error and the outcome follows a generalized linear model. Statistics in medicine, 33(28), 4875-4890.

Valeri, L., & Vanderweele, T. J. (2014). The estimation of direct and indirect causal effects in the presence of misclassified binary mediator. Biostatistics, 15(3), 498-512.

Valeri, L., Chen, J. T., Garcia-Albeniz, X., Krieger, N., VanderWeele, T. J., & Coull, B. A. (2016). The role of stage at diagnosis in colorectal cancer black-white survival disparities: a counterfactual causal inference approach. Cancer Epidemiology and Prevention Biomarkers, 25(1), 83-89.

Valeri, L., & Coull, B. A. (2016). Estimating causal contrasts involving intermediate variables in the presence of selection bias. Statistics in medicine, 35(26), 4779-4793.

Valeri, L., Mazumdar, M. M., Bobb, J. F., Claus Henn, B., Rodrigues, E., Sharif, O. I., ... & Amarasiriwardena, C. (2017). The joint effect of prenatal exposure to metal mixtures on neurodevelopmental outcomes at 20-40 months of age: evidence from rural Bangladesh. Environmental health perspectives, 125(6), 067015.

Valeri, L. (2017). Causal Mediation Analysis in Pregnancy Studies: the Case of Environmental Epigenetics. Current Epidemiology Reports, 4(2), 117-123.