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 Medjournal_title
Statistics in medicineauthors
Jung I,Kulldorff M,Klassen ACdoi
10.1002/sim.2607subject
Has Abstractpub_date
2007-03-30 00:00:00pages
1594-607issue
7eissn
0277-6715issn
1097-0258journal_volume
26pub_type
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