Abstract #300629

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JSM 2003 Abstract #300629
Activity Number: 373
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300629
Title: A Spatial Scan Statistic for Survival Data
Author(s): Lan Huang*+ and Martin Kulldorff and David Gregorio
Companies: University of Connecticut and University of Connecticut and University of Connecticut
Address: 215 Glenbrook Rd., Storrs, CT, 06269,
Keywords: geographical surveillance ; spatial scan statistic ; exponential model ; survival data ; censoring ; covariate adjustment
Abstract:

Spatial scan statistics with Bernoulli and Poisson models are commonly used for geographical disease surveillance and cluster detection. These models are suitable for count data, but were not designed for continuous data. We propose a spatial scan statistic based on an exponential model to be used for uncensored or censored survival data. The method performs well for different survival distribution functions including the exponential and gamma distributions. How to adjust the analysis for covariates is discussed in detail. The method is illustrated using survival data for men diagnosed with prostate cancer in Connecticut from 1984 to 1995.

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