Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/58973
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dc.contributor.authorvan den Berg, Gerard J.en_US
dc.contributor.authorDrepper, Bettinaen_US
dc.date.accessioned2012-04-03en_US
dc.date.accessioned2012-06-15T07:59:18Z-
dc.date.available2012-06-15T07:59:18Z-
dc.date.issued2011en_US
dc.identifier.piurn:nbn:de:101:1-201110263752-
dc.identifier.urihttp://hdl.handle.net/10419/58973-
dc.description.abstractShared-frailty survival models specify that systematic unobserved determinants of duration outcomes are identical within groups of individuals. We consider random-effects likelihood-based statistical inference if the duration data are subject to left-truncation. Such inference with left-truncated data can be performed in the Stata software package. We show that with left-truncated data, the commands ignore the weeding-out process before the left-truncation points, affecting the distribution of unobserved determinants among group members in the data, that is, among the group members who survive until their truncation points. We critically examine studies in the statistical literature on this issue as well as published empirical studies that use the commands. Simulations illustrate the size of the (asymptotic) bias and its dependence on the degree of truncation. We provide a Stata command file that maximizes the likelihood function that properly takes account of the interplay between truncation and dynamic selection.en_US
dc.language.isoengen_US
dc.publisher|aInstitute for the Study of Labor (IZA) |cBonnen_US
dc.relation.ispartofseries|aDiscussion Paper series, Forschungsinstitut zur Zukunft der Arbeit |x6031en_US
dc.subject.jelC41en_US
dc.subject.jelC34en_US
dc.subject.ddc330en_US
dc.subject.keywordstataen_US
dc.subject.keywordduration analysisen_US
dc.subject.keywordleft-truncationen_US
dc.subject.keywordlikelihood functionen_US
dc.subject.keyworddynamic selectionen_US
dc.subject.keywordhazard rateen_US
dc.subject.keywordunobserved heterogeneityen_US
dc.subject.keywordtwin dataen_US
dc.subject.stwStatistische Bestandsanalyseen_US
dc.subject.stwInferenzstatistiken_US
dc.subject.stwMaximum-Likelihood-Methodeen_US
dc.titleInference for shared-frailty survival models with left-truncated dataen_US
dc.typeWorking Paperen_US
dc.identifier.ppn68959772Xen_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US

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