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Modified spatial scan statistics using a restricted likelihood ratio for ordinal outcome data

Authors
 Myeonggyun Lee  ;  Inkyung Jung 
Citation
 COMPUTATIONAL STATISTICS & DATA ANALYSIS, Vol.133 : 28-39, 2019 
Journal Title
 COMPUTATIONAL STATISTICS & DATA ANALYSIS 
ISSN
 0167-9473 
Issue Date
2019
Abstract
Spatial scan statistics are widely used as a technique to detect geographical disease clusters for different types of data. It has been pointed out that the Poisson-based spatial scan statistic tends to detect rather larger clusters by absorbing insignificant neighbors with non-elevated risks. We suspect that the spatial scan statistic for ordinal data may also have similar undesirable phenomena. In this paper, we propose to apply a restricted likelihood ratio to spatial scan statistics for ordinal outcome data to circumvent such a phenomenon. Through a simulation study, we demonstrated not only that original spatial scan statistics have the over-detection phenomenon but also that our proposed methods have reasonable or better performance compared with the original methods. We illustrated the proposed methods using a real data set from the 2014 Health Screening Program of Korea with the diagnosis results of normal, caution, suspected disease, and diagnosed with disease as an ordinal outcome.
Full Text
https://www.sciencedirect.com/science/article/pii/S0167947318302330
DOI
10.1016/j.csda.2018.09.005
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers
Yonsei Authors
Jung, Inkyung(정인경) ORCID logo https://orcid.org/0000-0003-3780-3213
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/169423
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