Spatial cluster detection for censored outcome data.
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 Statistics 26, 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.
Cook
Andrea J
AJ
Department of Biostatistics, University of Washington, Seattle, Washington 98105, USA. acook@u.washington.edu
Gold
Diane R
DR
Li
Yi
Y
D000485:Allergens; D001249:Asthma / Q000453:epidemiology / Q000209:etiology; D001699:Biometry / Q000379:methods*; D002648:Child; D016000:Cluster Analysis; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D004781:Environmental Exposure; D006801:Humans; D008404:Massachusetts / Q000453:epidemiology; D015233:Models, Statistical; D016016:Proportional Hazards Models; D011446:Prospective Studies
D000485:Allergens