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Activity Number: 43
Type: Contributed
Date/Time: Sunday, August 3, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #311843 View Presentation
Title: Detecting Cancer Incidence in the Annual Surveillance Data Submission
Author(s): Li Zhu*+ and Linda Pickle and Jim Pearson
Companies: NIH and StatNet Consulting and StatNet Consulting
Keywords: SEER ; SaTScan ; R package ; Spatio-temporal ; Scan Statistics
Abstract:

The National Cancer Institute releases new cancer cases and burdens with the annual SEER data and Cancer Statistics Review. This project is to apply the spatio-temporal scan software SaTScan to detect new space-time clusters in the annual cancer incidence data. The analysis is done at the census tract level to allow for the maximum flexibility in the shape and size of the detect clusters. Various features in SaTScan, including statistical models,adjustment in expected values, and spatial and temporal adjustments, are explored for the purpose of this project. An R package is developed to create user-friendly map and text reports for the findings. The R package is also expanded so that users with similar task can put in their own data to create reports.


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