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- W2892477438 abstract "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." @default.
- W2892477438 created "2018-10-05" @default.
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- W2892477438 date "2019-05-01" @default.
- W2892477438 modified "2023-09-24" @default.
- W2892477438 title "Modified spatial scan statistics using a restricted likelihood ratio for ordinal outcome data" @default.
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- W2892477438 doi "https://doi.org/10.1016/j.csda.2018.09.005" @default.
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