{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T12:20:26Z","timestamp":1772194826932,"version":"3.50.1"},"reference-count":25,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2005,2,1]],"date-time":"2005-02-01T00:00:00Z","timestamp":1107216000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2005,2]]},"abstract":"<jats:p> This article discusses and extends statistical models to jointly analyse the spatial variation of rates of several diseases with common risk factors. We start with a review of methods for separate analyses of diseases, then move to ecological regression approaches, where the rates from one of the diseases enter as surrogate covariates for exposure. Finally, we propose a general framework for jointly modelling the variation of two or more diseases, some of which share latent spatial fields, but with possibly different risk gradients. In our application, we consider mortality data on oral, oesophagus, larynx and lung cancers for males in Germany, which all share smoking as a common risk factor. Furthermore, the first three cancers are also known to be related to excessive alcohol consumption. An empirical comparison of the different models based on a formal model criterion as well as on the posterior precision of the relative risk estimates strongly suggests that the joint modelling approach is a useful and valuable extension over individual analyses. <\/jats:p>","DOI":"10.1191\/0962280205sm389oa","type":"journal-article","created":{"date-parts":[[2005,1,8]],"date-time":"2005-01-08T02:50:06Z","timestamp":1105152606000},"page":"61-82","source":"Crossref","is-referenced-by-count":128,"title":["Towards joint disease mapping"],"prefix":"10.1177","volume":"14","author":[{"given":"Leonhard","family":"Held","sequence":"first","affiliation":[{"name":"Department of Statistics, University of Munich, Germany,"}]},{"given":"Isabel","family":"Nat\u00e1rio","sequence":"additional","affiliation":[{"name":"CEAUL, Faculdade de Ci\u00eancias da Universidade de Lisboa and                         Faculdade de Ci\u00eancias e Tecnologia da Universidade Nova de Lisboa, Portugal"}]},{"given":"Sarah Elaine","family":"Fenton","sequence":"additional","affiliation":[{"name":"Department of Veterinary Clinical Sciences and Department of Mathematical                         Sciences, University of Liverpool, UK"}]},{"given":"H\u00e5vard","family":"Rue","sequence":"additional","affiliation":[{"name":"Department of Mathematical Sciences, Norwegian University of Science and                         Technology, Trondheim, Norway"}]},{"given":"Nikolaus","family":"Becker","sequence":"additional","affiliation":[{"name":"German Cancer Research Center, Heidelberg, Germany"}]}],"member":"179","published-online":{"date-parts":[[2005,2,1]]},"reference":[{"key":"atypb1","first-page":"253","volume":"48","author":"Langford IH","year":"1999","journal-title":"Applied Statistics"},{"key":"atypb2","doi-asserted-by":"publisher","DOI":"10.1002\/1097-0258(20000915\/30)19:17\/18<2469::AID-SIM582>3.0.CO;2-4"},{"key":"atypb3","first-page":"59","volume-title":"The Yearbook of the Finnish Statistical Society, 1999-2000","author":"Knorr-Held L.","year":"2000"},{"key":"atypb4","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116466"},{"key":"atypb5","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2000.00013.x"},{"key":"atypb6","doi-asserted-by":"publisher","DOI":"10.1111\/1467-985X.00187"},{"key":"atypb7","doi-asserted-by":"publisher","DOI":"10.1198\/016214501753382408"},{"key":"atypb8","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1097-0258(19970415)16:7<741::AID-SIM501>3.0.CO;2-1"},{"key":"atypb9","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00353"},{"key":"atypb10","unstructured":"Fenton SE. 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