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| Project Title | Statistical Methods for Estimating Causal Risk Differences (PRISM) |
| Date Posted |
3-08-2012
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| Project 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.
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| Workgroup Leader(s) | Andrea J. Cook, PhD, Biostatistics Unit, Group Health Research Institute and Department of Biostatistics, University of Washington, Seattle, WA |
| Workgroup Members | 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, U.S. Food and Drug Administration, Silver Spring, MD; Michael D. Nguyen, MD, Estelle Russek-Cohen, PhD, and Zhen Jiang, PhD, Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD; Jennifer C. Nelson, PhD, Biostatistics Unit, Group Health Research Institute and Department of Biostatistics, University of Washington, Seattle, WA |
| Data Sources | |
| Deliverables |
Mini-Sentinel (PRISM) Statistical Methods for Estimating Causal Risk Differences.pdf
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| Related Links |
examplecode.R.txt
gendata.R.txt
IPWseqmethods.R.txt
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| Keywords | Mini-Sentinel, PRISM, statistical methods, estimation, causal risk differences, distributed data, postmarket safety surveillance, Cook, Wellman, Marsh, Tiwari, Nguyen, Russek-Cohen, Jiang, Nelson |
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