Mini-Sentinel: Statistical Methods for Estimating Causal Risk Differences (PRISM)

    Basic Details
    Date Posted
    Wednesday, March 7, 2012
    Status
    Complete
    Description

    Project to develop a new method for the distributed data setting to control for multiple confounders in the concurrent control design with a single time exposure, e.g., vaccine, assessing elevated rates of rare acute outcomes when the quantity of interest is a risk difference. The method proposed is applicable to both a single-time analysis and a group sequential analysis design.

    The programming code provided here has not been formally audited in accordance with the Mini-Sentinel Standard Operating Procedure for Quality Control of SAS Programs. It is being provided in the spirit of supporting the exploration and development of novel scientific and statistical methods using observational healthcare data.

    Workgroup Leader(s)

    Andrea J. Cook, PhD; Biostatistics Unit, Group Health Research Institute and Department of Biostatistics, University of Washington, Seattle, WA

    Workgroup Member(s)

    Robert D. Wellman, MS; Biostatistics Unit, Group Health Research Institute, Seattle, WA

    Tracey L. Marsh, MS; Department of Biostatistics, University of Washington and Group Health Research Institute, Seattle, WA

    Ram C. Tiwari, PhD; Office of Biostatistics, Center for Drug Evaluation and Research, FDA, Silver Spring, MD

    Jennifer C. Nelson, PhD; Biostatistics Unit, Group Health Research Institute and Department of Biostatistics, University of Washington, Seattle, WA

    Michael D. Nguyen, MD; Estelle Russek-Cohen, PhD; Zhen Jiang, PhD; Center for Biologics Evaluation and Research, FDA, Silver Spring, MD