@article{ref1,
title="Spatial Cluster Detection for Censored Outcome Data",
journal="Biometrics",
year="2007",
author="Cook, Andrea J. and Gold, Diane R. and Li, Yi",
volume="63",
number="2",
pages="540-549",
abstract="Summary While numerous methods have been proposed to test for spatial cluster detection, in particular for discrete outcome data (e.g., disease incidence), few have been available for continuous data that are subject to censoring. This article provides an extension of the spatial scan statistic (Kulldorff, 1997, Communications in Statistics26, 1481–1496) for censored outcome data and further proposes a simple spatial cluster detection method by utilizing cumulative martingale residuals within the framework of the Cox's proportional hazards models. Simulations have indicated good performance of the proposed methods, with the practical applicability illustrated by an ongoing epidemiology study which investigates the relationship of environmental exposures to asthma, allergic rhinitis/hayfever, and eczema.<p />",
language="",
issn="0006-341X",
doi="10.1111/j.1541-0420.2006.00714.x",
url="http://dx.doi.org/10.1111/j.1541-0420.2006.00714.x"
}