Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
1992-9-8
pubmed:abstractText
This paper attempts to demonstrate the utility of cluster analysis as a descriptive method of studying mortality in epidemiology. In order to verify which algorithms of clustering best fit the data structure, the method of cophenetic correlation was implemented. Furthermore the probabilistic algorithm proposed by Beale was used to assess the partition. The results show the presence of some striking clusters between Local Sanitary Units of the Emilia Romagna Region for four types of tumour in men.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0393-2990
pubmed:author
pubmed:issnType
Print
pubmed:volume
8
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
222-7
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
1992
pubmed:articleTitle
Identification of homogeneous geographical areas of mortality for tumours from cluster analysis.
pubmed:affiliation
Chair of Biometric and Medical Statistics, University of Modena, Italy.
pubmed:publicationType
Journal Article