Linked Life Data

14969474

Source:http://linkedlifedata.com/resource/pubmed/id/14969474

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2004-2-18
pubmed:abstractText
Beta-binomial models are widely used for overdispersed binomial data, with the binomial success probability modeled as following a beta distribution. The number of binary trials in each binomial is assumed to be nonrandom and unrelated to the success probability. In many behavioral studies, however, binomial observations demonstrate more complex structures. In this article, a general beta-binomial-Poisson mixture model is developed, to allow for a relation between the number of trials and the success probability for overdispersed binomial data. An EM algorithm is implemented to compute both the maximum likelihood estimates of the model parameters and the corresponding standard errors. For illustration, the methodology is applied to study the feeding behavior of green-backed herons in two southeastern Missouri streams.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
59
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
955-61
pubmed:dateRevised
2004-11-17
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Modeling the dependence between number of trials and success probability in beta-binomial-Poisson mixture distributions.
pubmed:affiliation
Department of Statistics, University of Wisconsin-Madison, USA.
pubmed:publicationType
Journal Article