Literature DB >> 15690998

Empirical Bayes methods for disease mapping.

Alastair H Leyland1, Carolyn A Davies.   

Abstract

This paper reviews empirical Bayes methods for disease mapping. A distinction is made between spatial models (which take into account the geographical distribution of disease) and nonspatial models. Several estimators are presented, and methods of estimation are described. Empirical Bayes methods are compared with full Bayes methods, and we argue that both have their place.

Mesh:

Year:  2005        PMID: 15690998     DOI: 10.1191/0962280205sm387oa

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  19 in total

1.  Mapping health data: improved privacy protection with donut method geomasking.

Authors:  Kristen H Hampton; Molly K Fitch; William B Allshouse; Irene A Doherty; Dionne C Gesink; Peter A Leone; Marc L Serre; William C Miller
Journal:  Am J Epidemiol       Date:  2010-09-03       Impact factor: 4.897

2.  Comparison of estimation methods for creating small area rates of acute myocardial infarction among Medicare beneficiaries in California.

Authors:  Laura C Yasaitis; Mariana C Arcaya; S V Subramanian
Journal:  Health Place       Date:  2015-09-15       Impact factor: 4.078

3.  Estimating Country-Specific Incidence Rates of Rare Cancers: Comparative Performance Analysis of Modeling Approaches Using European Cancer Registry Data.

Authors:  Diego Salmerón; Laura Botta; José Miguel Martínez; Annalisa Trama; Gemma Gatta; Josep M Borràs; Riccardo Capocaccia; Ramon Clèries
Journal:  Am J Epidemiol       Date:  2022-02-19       Impact factor: 4.897

4.  POISSON COKRIGING AS A GENERALIZED LINEAR MIXED MODEL.

Authors:  Lynette M Smith; Walter W Stroup; David B Marx
Journal:  Spat Stat       Date:  2019-12-13

5.  Power Evaluation of Focused Cluster Tests.

Authors:  Rc Puett; Ab Lawson; Ab Clark; Jr Hebert; M Kulldorff
Journal:  Environ Ecol Stat       Date:  2010-09       Impact factor: 1.119

6.  Socioeconomic Predictors of Trends in Cancer Mortality among Municipalities in Japan, 2010-2019.

Authors:  Tasuku Okui
Journal:  Asian Pac J Cancer Prev       Date:  2021-02-01

7.  Adjusting for sampling variability in sparse data: geostatistical approaches to disease mapping.

Authors:  Kristen H Hampton; Marc L Serre; Dionne C Gesink; Christopher D Pilcher; William C Miller
Journal:  Int J Health Geogr       Date:  2011-10-06       Impact factor: 3.918

8.  Corrected and Republished from: Socioeconomic Predictors of Trends in Cancer Mortality Among Municipalities in Japan, 2010-2019.

Authors:  Tasuku Okui
Journal:  Asian Pac J Cancer Prev       Date:  2022-01-01

9.  Geostatistical analysis of disease data: estimation of cancer mortality risk from empirical frequencies using Poisson kriging.

Authors:  Pierre Goovaerts
Journal:  Int J Health Geogr       Date:  2005-12-14       Impact factor: 3.918

10.  Cancer incidence in men: a cluster analysis of spatial patterns.

Authors:  Tiziana Cassetti; Francesco La Rosa; Luca Rossi; Daniela D'Alò; Fabrizio Stracci
Journal:  BMC Cancer       Date:  2008-11-25       Impact factor: 4.430

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