Linked Life Data

12197299

Source:http://linkedlifedata.com/resource/pubmed/id/12197299

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2002-8-28
pubmed:abstractText
Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommended use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0962-2802
pubmed:author
pubmed:issnType
Print
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
317-25
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Mixture models for quantitative HIV RNA data.
pubmed:affiliation
Departments of International Health and Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Mayland, USA. LMOULTON@JHSPH.EDU
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't