{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T21:21:02Z","timestamp":1777929662771,"version":"3.51.4"},"reference-count":28,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2016,8,1]],"date-time":"2016-08-01T00:00:00Z","timestamp":1470009600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Stat Methods Med Res"],"published-print":{"date-parts":[[2016,8]]},"abstract":"<jats:p>Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by \u201csimilarity\u201d with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models.<\/jats:p>","DOI":"10.1177\/0962280216660407","type":"journal-article","created":{"date-parts":[[2016,8,26]],"date-time":"2016-08-26T08:08:29Z","timestamp":1472198909000},"page":"1166-1184","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping"],"prefix":"10.1177","volume":"25","author":[{"given":"Helena","family":"Baptista","sequence":"first","affiliation":[{"name":"NOVA Information Management School, Universidade Nova de Lisboa, Lisboa, Portugal"}]},{"given":"Jorge M","family":"Mendes","sequence":"additional","affiliation":[{"name":"NOVA Information Management School, Universidade Nova de Lisboa, Lisboa, Portugal"}]},{"given":"Ying C","family":"MacNab","sequence":"additional","affiliation":[{"name":"Epidemiology and Biostatistics, School of Population and Public Health, University of British Columbia, Vancouver, Canada"}]},{"given":"Miguel","family":"Xavier","sequence":"additional","affiliation":[{"name":"Chronic Diseases Research Center (CEDOC) and Department of Mental Health, NOVA Medical School, Universidade Nova de Lisboa, Lisboa, Portugal"}]},{"given":"Jos\u00e9","family":"Caldas-de-Almeida","sequence":"additional","affiliation":[{"name":"Chronic Diseases Research Center (CEDOC) and Department of Mental Health, NOVA Medical School, Universidade Nova de Lisboa, Lisboa, Portugal"}]}],"member":"179","published-online":{"date-parts":[[2016,8,26]]},"reference":[{"key":"bibr1-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1007\/BF00116466"},{"key":"bibr2-0962280216660407","first-page":"65","volume-title":"Practical handbook of spatial statistics","author":"Griffith DA","year":"1996"},{"key":"bibr3-0962280216660407","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1111\/j.2517-6161.1974.tb00999.x","volume":"36","author":"Besag J","year":"1974","journal-title":"J R Stat Soc"},{"key":"bibr4-0962280216660407","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1093\/oso\/9780198504856.003.0006","volume-title":"Bayesian statistics 6","author":"Best N","year":"1999"},{"key":"bibr5-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1186\/1476-072X-6-54"},{"key":"bibr6-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1016\/j.stamet.2008.02.005"},{"key":"bibr7-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1111\/rssc.12009"},{"key":"bibr8-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1111\/j.1521-0391.2013.12082.x"},{"key":"bibr9-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1186\/1752-4458-7-19"},{"key":"bibr10-0962280216660407","first-page":"79","volume":"13","author":"Baptista H","year":"2015","journal-title":"REVSTAT"},{"key":"bibr11-0962280216660407","unstructured":"WHO.\n                      Global Status Report on alcohol and health\n                      . Technical report, WHO, 2014."},{"key":"bibr12-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0050141"},{"key":"bibr13-0962280216660407","volume-title":"Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition)","author":"American Psychiatric Association","year":"1994","edition":"4"},{"key":"bibr14-0962280216660407","volume-title":"Encyclopaedia of nationalism","author":"Leoussi AS","year":"2001"},{"key":"bibr15-0962280216660407","unstructured":"Balsa C, Vital C and Pascueiro L.\n                      O consumo de bebidas alco\u00f3licas em Portugal Preval\u00eancias e padr\u00f5es de consumo, 2001\u20132007\n                      . Technical report, IDT; CesNova-Centro de estudos em sociologia, faculdade de Ci\u00eancias Sociais e Humanas, Universidade Nova de Lisboa, Lisbon, 2011."},{"key":"bibr16-0962280216660407","first-page":"122","volume":"6736","author":"Connor JP","year":"2015","journal-title":"The Lancet"},{"key":"bibr17-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1177\/0962280210371561"},{"key":"bibr18-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1016\/j.sste.2011.03.001"},{"key":"bibr19-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1201\/9781420010404"},{"key":"bibr20-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/37.1-2.17"},{"key":"bibr21-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.301.6759.1031"},{"key":"bibr22-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1201\/9781420072884-c29"},{"key":"bibr23-0962280216660407","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v055.i13"},{"key":"bibr24-0962280216660407","first-page":"169","volume-title":"Bayesian statistics","author":"Geweke J","year":"1992"},{"key":"bibr25-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1214\/06-BA117A"},{"key":"bibr26-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9868.00353"},{"key":"bibr27-0962280216660407","doi-asserted-by":"publisher","DOI":"10.1177\/0962280214527386"},{"key":"bibr28-0962280216660407","volume-title":"Bayesian disease mapping hierarchical modeling in spatial epidemiology","author":"Lawson AB","year":"2009"}],"container-title":["Statistical Methods in Medical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280216660407","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/0962280216660407","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/0962280216660407","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T23:49:04Z","timestamp":1777679344000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/0962280216660407"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8]]},"references-count":28,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2016,8]]}},"alternative-id":["10.1177\/0962280216660407"],"URL":"https:\/\/doi.org\/10.1177\/0962280216660407","relation":{},"ISSN":["0962-2802","1477-0334"],"issn-type":[{"value":"0962-2802","type":"print"},{"value":"1477-0334","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8]]}}}