Overview
Carly L. Brantner, PhD, joined the Department of Biostatistics and Bioinformatics and the Duke Clinical Research Institute in 2024. She is both a methodological and collaborative biostatistician. Her methodological background primarily centers around causal inference, focusing on developing and adapting machine learning methods to integrate multiple data sources and estimate heterogeneous treatment effects. She is particularly interested in aiding efficient and effective personalized treatment decisions through robust statistical approaches. She is passionate about impacting health across many areas, including but not limited to female health, mental health, sport science, musculoskeletal systems and function, and aging.
Current Appointments & Affiliations
Assistant Professor of Biostatistics & Bioinformatics
·
2024 - Present
Biostatistics & Bioinformatics, Division of Biostatistics,
Biostatistics & Bioinformatics
Member in the Duke Clinical Research Institute
·
2024 - Present
Duke Clinical Research Institute,
Institutes and Centers
Recent Publications
Precision Mental Health: Predicting Heterogeneous Treatment Effects for Depression through Data Integration.
Journal Article J R Stat Soc Ser C Appl Stat · December 12, 2025 When treating depression, clinicians are interested in determining the optimal treatment for a given patient, which is challenging given the amount of treatments available. To advance individualized treatment allocation, integrating data across multiple ra ... Full text Link to item CiteGaps in psychiatric care before and after the COVID-19 pandemic among patients with depression using electronic health records.
Journal Article Psychiatry Res · February 2025 The COVID-19 pandemic caused disruption to health services. It is unclear if there were inequalities in the continuity of mental health care in the years around the COVID-19 pandemic. We used electronic health records (EHR) to detect mental health care gap ... Full text Link to item CiteThe challenges of integrating diverse data sources: A case study in major depression
Journal Article Health Services and Outcomes Research Methodology · January 1, 2025 Combining data from diverse sources including randomized controlled trials (RCTs) and observational datasets holds the potential to increase sample size, improve external validity, and gain a well-rounded view of the question under study. However, the prac ... Full text CiteRecent Grants
PCORNet Statment 9: Representativeness
ResearchCo Investigator · Awarded by Patient-Centered Outcomes Research Institute · 2024 - 2026View All Grants
Education, Training & Certifications
Johns Hopkins Unversity, Bloomberg School of Public Health ·
2024
Ph.D.