Seminars

  • Ludovic Trinquart, PhD
    Dec
    9
    3:00pm - 4:00pm

    Statistics C. V. Starr Lecture - Ludovic Trinquart, PhD

    121 South Main Street, Room 245

    Ludovic Trinquart PhD, Assistant Professor of Biostatistics, Boston University School of Public Health

    “Counterfactual mediation analysis with illness-death model for right-censored surrogate and clinical outcomes”

    We introduce a counterfactual-based mediation analysis for surrogate outcome evaluation when both the surrogate and clinical endpoint are subject to right-censoring. We use a multistate model for risk prediction to account for both direct transitions towards the clinical endpoint and transitions through the surrogate endpoint. We use the counterfactual framework to define natural direct and indirect effects and the proportion of the treatment effect on the clinical endpoint mediated by the surrogate endpoint. We define these quantities for the cumulative risk and restricted mean survival time. We illustrate our approach using 18-year follow-up data from the SPCG-4 randomized controlled trial of radical prostatectomy for prostate cancer. We assess time to metastasis as a potential surrogate outcome for all-cause mortality.

    Biology, Medicine, Public Health, BioStatsSeminar, Education, Teaching, Instruction, Graduate School, Postgraduate Education, Mathematics, Technology, Engineering, Training, Professional Development
  • Sumithra Mandrekar, PhD
    Mar
    9
    3:00pm - 4:00pm

    Statistics C. V. Starr Lecture: Sumithra Mandrekar, PhD

    121 South Main Street, Room 245

    Sumithra Mandrekar, PhD, Professor of Biostatistics and Oncology, Mayo Clinic; Section Head, Cancer Center Statistics at the Mayo Clinic Department of Health Sciences Research, Rochester, MN

    Title and Abstract to be announced

    Biology, Medicine, Public Health, BioStatsSeminar, Education, Teaching, Instruction, Graduate School, Postgraduate Education, Mathematics, Technology, Engineering, Training, Professional Development
  • Andrey Fedorov, PhD
    Mar
    16
    3:00pm - 4:00pm

    Statistics Seminar, Andrey Fedorov, PhD

    121 South Main Street, Room 245

    Andrey Fedorov, PhD, Assistant Professor in Radiology, Surgical Planning Laboratory, Department  of Radiology, Brigham and Women’s Hospital, Harvard Medical School

    Abstract to be posted

    Title:  Managing Data for Medical Image Computing Research

    Bio:  Andrey joined SPL in 2009 after obtaining his PhD in Computer Science from The College of William and Mary in Virginia. His research is in translation and validation of medical image computing technology in clinical research applications, with the focus on quantitative imaging, imaging informatics and image-guided interventional procedures. Andrey is committed to advancing the role of reproducible science, data sharing and open source software in academic research. He has contributed to several open source projects, most notably 3D Slicer (http://slicer.org ) and dcmqi (https://github.com/qiicr/dcmqi ).
    Together with Ron Kikinis, he served as a co-PI of the Quantitative
    Image Informatics for Cancer Research (QIICR) project
    (http://qiicr.org ) funded by NCI. Andrey is a technical lead for the
    consortium developing Imaging Data Commons (IDC) node for the NCI Cancer Research Data Commons (CRDC) platform. The IDC will be a cloud-based resource that connects researchers with 1) cancer image collections, 2) a robust infrastructure that contains imaging data, subject and sample metadata and experimental metadata from disparate sources, 3) resources for searching, identifying and viewing images, and 4) additional data types contained in other Cancer Research Data Commons nodes.

    Biology, Medicine, Public Health, BioStatsSeminar, Education, Teaching, Instruction, Graduate School, Postgraduate Education, Mathematics, Technology, Engineering, Training, Professional Development
  • Daniel Almirall, PhD
    Apr
    6
    3:00pm - 4:00pm

    Statistics C. V. Starr Lecture, Daniel Almirall, PhD

    121 South Main Street, Room 245

    Daniel Almirall, PhD, Associate Professor, Co-Director, Data Science for Dynamic Intervention Decision-making Laboratory (d3lab), Survey Research Center, Institute for Social Research; Department of Statistics, College of Literature Sciences and the Arts, University of Michigan

    Bio: Daniel Almirallis Associate Professor in the Institute for Social Research and the Department of Statistics at the University of Michigan. He is a methodologist and statistician who develops methods to form evidence-based adaptive interventions. Adaptive interventions can be used to inform individualized intervention guidelines for the on-going management of chronic illnesses or disorders such as drug abuse, depression, anxiety, autism, obesity, or HIV/AIDS. More recently, Dr. Almirall has been developing methods to form adaptive implementation interventions, to inform how best to tailor sequences of organizational-level strategies to improve the implementation of evidence-based practices. His work includes the development of approaches related to the design, execution, and analysis of sequential multiple assignment randomized trials (SMARTs) which can be used to build adaptive interventions, and of clustered SMARTs to build adaptive implementation interventions. He is particularly interested in applications in child and adolescent mental health research.

    Abstract to be posted

    Biology, Medicine, Public Health, BioStatsSeminar, Education, Teaching, Instruction, Graduate School, Postgraduate Education, Mathematics, Technology, Engineering, Training, Professional Development
  • Bonnie Ghosh-Dastidar, PhD
    Apr
    20
    3:00pm - 4:00pm

    Statistics Seminar - Bonnie Ghosh-Dastidar, PhD

    121 South Main Street, Room 245

    Bonnie Ghosh-Dastidar, PhD, Senior Statistician, RAND Corporation, Head of the RAND Statistics Group

    Title:  “Outcome-Optimized Nonresponse Weighting”

    Abstract to be posted

    Biology, Medicine, Public Health, BioStatsSeminar, Education, Teaching, Instruction, Graduate School, Postgraduate Education, Mathematics, Technology, Engineering, Training, Professional Development