Skip to main content

Spatial Cluster Detection for Censored Outcome Data

Buy Article:

$51.00 plus tax (Refund Policy)



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.

Keywords: Asthma; Cluster detection; Cumulative residuals; Martingales; Spatial scan statistic

Document Type: Research Article


Affiliations: 1: The Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, U.S.A. 2: Department of Biostatistics, Harvard School of Public Health and the Dana Farber Cancer Institute, Boston, Massachusetts 02115, U.S.A.

Publication date: June 1, 2007

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Partial Open Access Content
Partial Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more