A spatial scan statistic for ordinal data.

Abstract:

:Spatial scan statistics are widely used for count data to detect geographical disease clusters of high or low incidence, mortality or prevalence and to evaluate their statistical significance. Some data are ordinal or continuous in nature, however, so that it is necessary to dichotomize the data to use a traditional scan statistic for count data. There is then a loss of information and the choice of cut-off point is often arbitrary. In this paper, we propose a spatial scan statistic for ordinal data, which allows us to analyse such data incorporating the ordinal structure without making any further assumptions. The test statistic is based on a likelihood ratio test and evaluated using Monte Carlo hypothesis testing. The proposed method is illustrated using prostate cancer grade and stage data from the Maryland Cancer Registry. The statistical power, sensitivity and positive predicted value of the test are examined through a simulation study.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Jung I,Kulldorff M,Klassen AC

doi

10.1002/sim.2607

subject

Has Abstract

pub_date

2007-03-30 00:00:00

pages

1594-607

issue

7

eissn

0277-6715

issn

1097-0258

journal_volume

26

pub_type

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