Source:http://linkedlifedata.com/resource/pubmed/id/15714631
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:dateCreated |
2005-2-15
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| pubmed:abstractText |
Statistical analysis of syndromic data has typically focused on univariate test statistics for spatial, temporal, or spatio-temporal surveillance. However, this approach does not take full advantage of the information available in the data.
|
| pubmed:grant | |
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
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| pubmed:month |
Sep
|
| pubmed:issn |
1545-861X
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| pubmed:author | |
| pubmed:issnType |
Electronic
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| pubmed:day |
24
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| pubmed:volume |
53 Suppl
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| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
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| pubmed:pagination |
59-66
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| pubmed:dateRevised |
2008-2-14
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| pubmed:meshHeading |
pubmed-meshheading:15714631-Cluster Analysis,
pubmed-meshheading:15714631-Demography,
pubmed-meshheading:15714631-Disease Outbreaks,
pubmed-meshheading:15714631-Epidemiologic Measurements,
pubmed-meshheading:15714631-Humans,
pubmed-meshheading:15714631-Models, Statistical,
pubmed-meshheading:15714631-Population Surveillance
|
| pubmed:year |
2004
|
| pubmed:articleTitle |
Bivariate method for spatio-temporal syndromic surveillance.
|
| pubmed:affiliation |
Department of Biostatistics, Harvard School of Public Health, 655 Huntington Avenue, Boston, MA 02115, USA. pagano@hsph.harvard.edu
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| pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, P.H.S.
|