Details
The aim of this project was to enhance TreeExtraction/CIDA software and TreeScan to enable sequential TreeScan analyses over time. This project developed adjustments to maintain multiplicity control in tree-based scan statistics (Unconditional Bernoulli) to account for sequentially arriving analytic datasets. These sequential adjustments were developed for the fixed-window self-controlled study design and the propensity score matched study design.
Contributors
Martin Kulldorff, PhD; Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital and 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
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