Identification

Author

Jung I, Kulldorff M, Klassen AC

Title

A spatial scan statistic for ordinal data

Year

2007

Publication type

Article

Journal

Statistics in Medicine

Created

2014-06-09 16:58:57+00:00

Modified

2016-06-29 16:33:42.336782+00:00

Details

Volume

26

Number

7

Access

Language

English

URL http://onlinelibrary.wiley.com/doi/10.1002/sim.2607/abstract
DOI

10.1002/sim.2607

Accessed

2016-06-29

Extended information

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.