Linked Life Data

17094075

Source:http://linkedlifedata.com/resource/pubmed/id/17094075

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
16
pubmed:dateCreated
2007-6-14
pubmed:abstractText
The proportional hazard (PH) mixture cure model and the accelerated failure time (AFT) mixture cure model are usually used in analysing failure time data with long-term survivors. However, the semiparametric AFT mixture cure model has attracted less attention than the semiparametric PH mixture cure model because of the complexity of its estimation method. In this paper, we propose a new estimation method for the semiparametric AFT mixture cure model. This method employs the EM algorithm and the rank estimator of the AFT model to estimate the parameters of interest. The M-step in the EM algorithm, which incorporates the rank-like estimating equation, can be carried out easily using the linear programming method. To evaluate the performance of the proposed method, we conduct a simulation study. The results of the simulation study demonstrate that the proposed method performs better than the existing estimation method and the semiparametric AFT mixture cure model improves the identifiability of the parameters in comparison to the parametric AFT mixture cure model. To illustrate, we apply the model and the proposed method to a data set of failure times from bone marrow transplant patients.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
0277-6715
pubmed:author
pubmed:copyrightInfo
(c) 2006 John Wiley & Sons, Ltd.
pubmed:issnType
Print
pubmed:day
20
pubmed:volume
26
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
3157-71
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
A new estimation method for the semiparametric accelerated failure time mixture cure model.
pubmed:affiliation
Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, NL, Canada A1C 5S7. jiajia@math.mun.ca
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't