Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1997-1-6
pubmed:abstractText
We explore the relationship between nutritive sucking behavior and physiological status of premature infants. Conventional statistical methods are no longer adequate in this context due to the highly complex structure of nutritive sucking data. We describe sucking pattern by a binary time series and propose a Markov regression model that relates the transition probabilities of the Markov chain to time-dependent covariates through a logistic linkage function. The model is fit to data collected at the Hospital of the University of Pennsylvania. The results are compared with those obtained from traditional data analysis.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
52
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
112-24
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
A Markov regression model for nutritive sucking data.
pubmed:affiliation
Department of Statistics, University of Pennsylvania, Philadelphia 19104, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't