Multiple testing in disease mapping and descriptive epidemiology

Catelan, Dolores and Biggeri, Annibale (2010) Multiple testing in disease mapping and descriptive epidemiology. Geospatial health , 4 (2). pp. 219-229. ISSN 1970-7096

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The problem of multiple testing is rarely addressed in disease mapping or descriptive epidemiology. This issue is relevant when a large number of small areas or diseases are analysed. Control of the family wise error rate (FWER), for example via the Bonferroni correction, is avoided because it leads to loss of statistical power. To overcome such difficulties, control of the false discovery rate (FDR), the expected proportion of false rejections among all rejected hypotheses, was proposed in the context of clinical trials and genomic data analysis. FDR has a Bayesian interpretation and it is the basis of the so called q-value, the Bayesian counterpart of the p-value. In the present work, we address the multiplicity problem in disease mapping and show the performance of the FDR approach with two real examples and a small simulation study. The examples consider testing multiple diseases for a given area or multiple areas for a given disease. Using unadjusted p-values for multiple testing, an inappropriately large number of areas or diseases at altered risk are identified, whilst FDR procedures are appropriate and more powerful than the control of the FWER with the Bonferroni correction. We conclude that the FDR approach is adequate to screen for high/low risk areas or for disease excess/deficit and useful as a complementary procedure to point estimates and confidence intervals.

Item Type: Article
Uncontrolled Keywords: descriptive epidemiology, disease mapping, small areas, multiple testing, false discovery rate.
Subjects: 600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici)
Depositing User: Emanuele Zinevrakis
Date Deposited: 05 Jul 2010 12:13
Last Modified: 05 Jul 2010 12:13

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