Modeling survival data with informative cluster size.
Identifieur interne : 002F21 ( PubMed/Checkpoint ); précédent : 002F20; suivant : 002F22Modeling survival data with informative cluster size.
Auteurs : John M. Williamson [États-Unis] ; Hae-Young Kim ; Amita Manatunga ; David G. AddissSource :
- Statistics in medicine [ 0277-6715 ] ; 2008.
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Abstract
Analysis of clustered data focusing on inference of the marginal distribution may be problematic when the risk of the outcome is related to the cluster size, termed as informative cluster size. In the absence of censoring, Hoffman et al. proposed a within-cluster resampling method, which is asymptotically equivalent to a weighted generalized estimating equations score equation. We investigate the estimation of the marginal distribution for multivariate survival data with informative cluster size using cluster-weighted Weibull and Cox proportional hazards models. The cluster-weighted Cox model can be implemented using standard software. Simulation results demonstrate that the proposed methods produce unbiased parameter estimation in the presence of informative cluster size. To illustrate the proposed approach, we analyze survival data from a lymphatic filariasis study in Recife, Brazil.
DOI: 10.1002/sim.3003
PubMed: 17640035
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Williamson</name><affiliation wicri:level="2"><nlm:affiliation>Division of Parasitic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, 4770 Buford Highway, NE, Atlanta, GA 30341, USA. jow5@cdc.gov</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Division of Parasitic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, 4770 Buford Highway, NE, Atlanta, GA 30341</wicri:regionArea><placeName><region type="state">Géorgie (États-Unis)</region></placeName></affiliation></author><author><name sortKey="Kim, Hae Young" sort="Kim, Hae Young" uniqKey="Kim H" first="Hae-Young" last="Kim">Hae-Young Kim</name></author><author><name sortKey="Manatunga, Amita" sort="Manatunga, Amita" uniqKey="Manatunga A" first="Amita" last="Manatunga">Amita Manatunga</name></author><author><name sortKey="Addiss, David G" sort="Addiss, David G" uniqKey="Addiss D" first="David G" last="Addiss">David G. Addiss</name></author></analytic><series><title level="j">Statistics in medicine</title><idno type="ISSN">0277-6715</idno><imprint><date when="2008" type="published">2008</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cluster Analysis</term><term>Elephantiasis, Filarial</term><term>Humans</term><term>Models, Statistical</term><term>Proportional Hazards Models</term><term>Survival Analysis</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de regroupements</term><term>Analyse de survie</term><term>Filariose lymphatique</term><term>Humains</term><term>Modèles de hasards proportionnels</term><term>Modèles statistiques</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cluster Analysis</term><term>Elephantiasis, Filarial</term><term>Humans</term><term>Models, Statistical</term><term>Proportional Hazards Models</term><term>Survival Analysis</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de regroupements</term><term>Analyse de survie</term><term>Filariose lymphatique</term><term>Humains</term><term>Modèles de hasards proportionnels</term><term>Modèles statistiques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Analysis of clustered data focusing on inference of the marginal distribution may be problematic when the risk of the outcome is related to the cluster size, termed as informative cluster size. In the absence of censoring, Hoffman et al. proposed a within-cluster resampling method, which is asymptotically equivalent to a weighted generalized estimating equations score equation. We investigate the estimation of the marginal distribution for multivariate survival data with informative cluster size using cluster-weighted Weibull and Cox proportional hazards models. The cluster-weighted Cox model can be implemented using standard software. Simulation results demonstrate that the proposed methods produce unbiased parameter estimation in the presence of informative cluster size. To illustrate the proposed approach, we analyze survival data from a lymphatic filariasis study in Recife, Brazil.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">17640035</PMID><DateCreated><Year>2008</Year><Month>01</Month><Day>15</Day></DateCreated><DateCompleted><Year>2008</Year><Month>06</Month><Day>17</Day></DateCompleted><DateRevised><Year>2008</Year><Month>01</Month><Day>15</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">0277-6715</ISSN><JournalIssue CitedMedium="Print"><Volume>27</Volume><Issue>4</Issue><PubDate><Year>2008</Year><Month>Feb</Month><Day>20</Day></PubDate></JournalIssue><Title>Statistics in medicine</Title><ISOAbbreviation>Stat Med</ISOAbbreviation></Journal><ArticleTitle>Modeling survival data with informative cluster size.</ArticleTitle><Pagination><MedlinePgn>543-55</MedlinePgn></Pagination><Abstract><AbstractText>Analysis of clustered data focusing on inference of the marginal distribution may be problematic when the risk of the outcome is related to the cluster size, termed as informative cluster size. In the absence of censoring, Hoffman et al. proposed a within-cluster resampling method, which is asymptotically equivalent to a weighted generalized estimating equations score equation. We investigate the estimation of the marginal distribution for multivariate survival data with informative cluster size using cluster-weighted Weibull and Cox proportional hazards models. The cluster-weighted Cox model can be implemented using standard software. Simulation results demonstrate that the proposed methods produce unbiased parameter estimation in the presence of informative cluster size. To illustrate the proposed approach, we analyze survival data from a lymphatic filariasis study in Recife, Brazil.</AbstractText><CopyrightInformation>2007 John Wiley & Sons, Ltd</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Williamson</LastName><ForeName>John M</ForeName><Initials>JM</Initials><AffiliationInfo><Affiliation>Division of Parasitic Diseases, National Center for Infectious Diseases, Centers for Disease Control and Prevention, 4770 Buford Highway, NE, Atlanta, GA 30341, USA. jow5@cdc.gov</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kim</LastName><ForeName>Hae-Young</ForeName><Initials>HY</Initials></Author><Author ValidYN="Y"><LastName>Manatunga</LastName><ForeName>Amita</ForeName><Initials>A</Initials></Author><Author ValidYN="Y"><LastName>Addiss</LastName><ForeName>David G</ForeName><Initials>DG</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Stat Med</MedlineTA><NlmUniqueID>8215016</NlmUniqueID><ISSNLinking>0277-6715</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D016000" MajorTopicYN="Y">Cluster Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D004605" MajorTopicYN="N">Elephantiasis, Filarial</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015233" MajorTopicYN="Y">Models, Statistical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016016" MajorTopicYN="N">Proportional Hazards Models</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016019" MajorTopicYN="Y">Survival Analysis</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2007</Year><Month>7</Month><Day>21</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2008</Year><Month>6</Month><Day>18</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2007</Year><Month>7</Month><Day>21</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">17640035</ArticleId><ArticleId IdType="doi">10.1002/sim.3003</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Géorgie (États-Unis)</li></region></list><tree><noCountry><name sortKey="Addiss, David G" sort="Addiss, David G" uniqKey="Addiss D" first="David G" last="Addiss">David G. Addiss</name><name sortKey="Kim, Hae Young" sort="Kim, Hae Young" uniqKey="Kim H" first="Hae-Young" last="Kim">Hae-Young Kim</name><name sortKey="Manatunga, Amita" sort="Manatunga, Amita" uniqKey="Manatunga A" first="Amita" last="Manatunga">Amita Manatunga</name></noCountry><country name="États-Unis"><region name="Géorgie (États-Unis)"><name sortKey="Williamson, John M" sort="Williamson, John M" uniqKey="Williamson J" first="John M" last="Williamson">John M. Williamson</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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