| pubmed-article:9878904 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:9878904 | lifeskim:mentions | umls-concept:C0014507 | lld:lifeskim |
| pubmed-article:9878904 | lifeskim:mentions | umls-concept:C1521828 | lld:lifeskim |
| pubmed-article:9878904 | lifeskim:mentions | umls-concept:C0024779 | lld:lifeskim |
| pubmed-article:9878904 | lifeskim:mentions | umls-concept:C0449445 | lld:lifeskim |
| pubmed-article:9878904 | pubmed:issue | 4 | lld:pubmed |
| pubmed-article:9878904 | pubmed:dateCreated | 1999-4-1 | lld:pubmed |
| pubmed-article:9878904 | pubmed:abstractText | This article presents statistical methods recently developed for the analysis of maps of disease rates when the geographic units have small populations at risk. They adopt the Bayesian approach and use intensive computational methods for estimating risk in each area. The objective of the methods is to separate the variability of rates due to differences between regions from the background risk due to pure random fluctuation. Risk estimates have a total mean quadratic error smaller than usual estimates. We apply these new methods to estimate infant mortality risk in the municipalities of the State of Minas Gerais in 1994. | lld:pubmed |
| pubmed-article:9878904 | pubmed:language | por | lld:pubmed |
| pubmed-article:9878904 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:9878904 | pubmed:citationSubset | IM | lld:pubmed |
| pubmed-article:9878904 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:9878904 | pubmed:issn | 0102-311X | lld:pubmed |
| pubmed-article:9878904 | pubmed:author | pubmed-author:SakuraiEE | lld:pubmed |
| pubmed-article:9878904 | pubmed:author | pubmed-author:GuerraH LHL | lld:pubmed |
| pubmed-article:9878904 | pubmed:author | pubmed-author:BarretoS MSM | lld:pubmed |
| pubmed-article:9878904 | pubmed:author | pubmed-author:AssunçãoR MRM | lld:pubmed |
| pubmed-article:9878904 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:9878904 | pubmed:volume | 14 | lld:pubmed |
| pubmed-article:9878904 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:9878904 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:9878904 | pubmed:pagination | 713-23 | lld:pubmed |
| pubmed-article:9878904 | pubmed:dateRevised | 2006-11-15 | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:meshHeading | pubmed-meshheading:9878904-... | lld:pubmed |
| pubmed-article:9878904 | pubmed:articleTitle | [Maps of epidemiological rates: a Bayesian approach]. | lld:pubmed |
| pubmed-article:9878904 | pubmed:affiliation | Departamento de Estatística, Universidade Federal de Minas Gerais, Caixa Postal 702, Belo Horizonte, MG 30161-970, Brasil. assuncao@est.ufmg.br | lld:pubmed |
| pubmed-article:9878904 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:9878904 | pubmed:publicationType | Comparative Study | lld:pubmed |
| pubmed-article:9878904 | pubmed:publicationType | English Abstract | lld:pubmed |
| pubmed-article:9878904 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
