Sequential TreeScan Signal Identification Methods Development

Project Title Sequential TreeScan Signal Identification Methods Development
Date Posted
Tuesday, December 11, 2018
Status
In progress
Description

The aim of this methods project is to enable and pilot test sequential TreeScan analyses over time.

This project will develop adjustments to tree-based scan statistics (Unconditional Bernoulli) that will enable sequential versions of TreeScan for the fixed-window self-controlled and propensity score matched approaches. Sequential TreeScan will also be performed on an agreed-upon example problem (i.e., a test case) in a non-distributed but routinely updated data source (Optum Clinformatics).

Workgroup Leader(s)

Martin Kulldorff PhD; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; Judith C. Maro PhD, Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA

Danijela Stojanovic PharmD, PhD; Office of Surveillance and Epidemiology, Center for Drug and Evaluation Research, US Food and Drug Administration, Silver Spring, MD

Workgroup Members

Elande Baro PhD; Sai Dharmarajan PhD; Office of Biostatistics, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD

Monica Munoz PharmD; Mallika Mundkur MD, MPH; Division of Pharmacovigilance, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD

Monique Falconer MD, MS; Richard S. Swain PhD, MPH; Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD.

Inna Dashevsky MS; Sandra DeLuccia MPH; Ella Pestine MPH; Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA