Identification

Author

Huang L, Kulldorff M, Gregorio D

Title

A spatial scan statistic for survival data

Year

2007

Publication type

Article

Journal

Biometrics

Created

2014-06-09 17:01:24+00:00

Modified

2016-08-09 20:17:06.322246+00:00

Details

Volume

63

Number

1

Access

Language

English

URL http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2006.00661.x/abstract
DOI

10.1111/j.1541-0420.2006.00661.x

Accessed

2016-06-29

Extended information

Abstract

Spatial scan statistics with Bernoulli and Poisson models are commonly used for geographical disease surveillance and cluster detection. These models, suitable for count data, were not designed for data with continuous outcomes. We propose a spatial scan statistic based on an exponential model to handle either uncensored or censored continuous survival data. The power and sensitivity of the developed model are investigated through intensive simulations. The method performs well for different survival distribution functions including the exponential, gamma, and log-normal distributions. We also present a method to adjust the analysis for covariates. The cluster detection method is illustrated using survival data for men diagnosed with prostate cancer in Connecticut from 1984 to 1995.