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Course 2: Causal Inference: Weighting Methods and Case Studies


Instructors

  • Hana  Lee, PhD

    Hana Lee, PhD

    • Statistical reviewer
    • FDA, United States

    Hana Lee, PhD, is a Biostatistician for the Office of Biostatistics in the Center for Drug Evaluation and Research at FDA. Her primary research interests focus on developing statistical methods for problems relating to the analysis of survival data obtained from cost-effective design, causal inference based on observational data, and clinical research on prescription opioid and AIDS therapies. She is currently working on reviewing post-marketing requirement studies relating to prescription opioid products, as well as planning and monitoring programs for data and method enhancement in this area.

  • Joo-Yeon  Lee, PhD, MA

    Joo-Yeon Lee, PhD, MA

    • Mathematical Statistician
    • FDA, United States

    Joo-Yeon Lee is a senior mathematical statistician in Division of Biometrics VII at FDA/CDER. Since she joined FDA in 2007, she developed an expertise on pharmacometrics and design and analysis of post-market drug safety studies. She has reviewed sponsor led studies as well as collaborated with other investigators in FDA-led studies in Sentinel Distributed System and federal data partners. She has played a leading role in causal inference method working group in Division of Biometrics VII. Prior to joining FDA, she earned Ph.D in Biostatistics from Brown University.

  • Laine  Thomas

    Laine Thomas

    • Assistant Professor of Biostatistics and Bioinformatics
    • Duke University, Department of Biostatistics and Bioinformatics , United States

    Dr. Thomas’ primary interest is causal inference methods, particularly using large data sets such as registries, Medicare claims and electronic health records. She is a co-investigator on the NIH-supported Statistical Methods for Complex Data in Cardiovascular Disease and primary investigator on the AHRQ-supported Matching Methods for Comparative Effectiveness Studies of Longitudinal Treatments. She uses causal inference methods in collaborations in cardiovascular disease (CHAMP-HF, ORBIT-AF registries; ACTION-NCDR and CRUSADE registries linked to Medicare; ARISTOTLE and NAVIGATOR clinical trials) and uterine fibroids (COMPARE-UF). She teaches the causal inference course in the Biostatistics and Bioinformatics Masters and PhD programs.