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Article: A NEW MULTILEVEL MODELING APPROACH FOR CLUSTERED SURVIVAL DATA

TitleA NEW MULTILEVEL MODELING APPROACH FOR CLUSTERED SURVIVAL DATA
Authors
Issue Date2020
PublisherCambridge University Press. The Journal's web site is located at http://journals.cambridge.org/action/displayJournal?jid=ECT
Citation
Econometric Theory, 2020, v. 36 n. 4, p. 707-750 How to Cite?
AbstractIn multilevel modeling of clustered survival data, to account for the differences among different clusters, a commonly used approach is to introduce cluster effects, either random or fixed, into the model. Modeling with random effects may lead to difficulties in the implementation of the estimation procedure for the unknown parameters of interest because the numerical computation of multiple integrals may become unavoidable when the cluster effects are not scalars. On the other hand, if fixed effects are used, there is a danger of having estimators with large variances because there are too many nuisance parameters involved in the model. In this article, using the idea of the homogeneity pursuit, we propose a new multilevel modeling approach for clustered survival data. The proposed modeling approach does not have the potential computational problem as modeling with random effects, and it also involves far fewer unknown parameters than modeling with fixed effects. We also establish asymptotic properties to show the advantages of the proposed model and conduct intensive simulation studies to demonstrate the performance of the proposed method. Finally, the proposed method is applied to analyze a dataset on the second-birth interval in Bangladesh. The most interesting finding is the impact of some important factors on the length of the second-birth interval variation over clusters and its homogeneous structure.
Persistent Identifierhttp://hdl.handle.net/10722/281706
ISSN
2023 Impact Factor: 1.0
2023 SCImago Journal Rankings: 1.393
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorXu, J-
dc.contributor.authorYue, M-
dc.contributor.authorZhang, W-
dc.date.accessioned2020-03-22T04:18:33Z-
dc.date.available2020-03-22T04:18:33Z-
dc.date.issued2020-
dc.identifier.citationEconometric Theory, 2020, v. 36 n. 4, p. 707-750-
dc.identifier.issn0266-4666-
dc.identifier.urihttp://hdl.handle.net/10722/281706-
dc.description.abstractIn multilevel modeling of clustered survival data, to account for the differences among different clusters, a commonly used approach is to introduce cluster effects, either random or fixed, into the model. Modeling with random effects may lead to difficulties in the implementation of the estimation procedure for the unknown parameters of interest because the numerical computation of multiple integrals may become unavoidable when the cluster effects are not scalars. On the other hand, if fixed effects are used, there is a danger of having estimators with large variances because there are too many nuisance parameters involved in the model. In this article, using the idea of the homogeneity pursuit, we propose a new multilevel modeling approach for clustered survival data. The proposed modeling approach does not have the potential computational problem as modeling with random effects, and it also involves far fewer unknown parameters than modeling with fixed effects. We also establish asymptotic properties to show the advantages of the proposed model and conduct intensive simulation studies to demonstrate the performance of the proposed method. Finally, the proposed method is applied to analyze a dataset on the second-birth interval in Bangladesh. The most interesting finding is the impact of some important factors on the length of the second-birth interval variation over clusters and its homogeneous structure.-
dc.languageeng-
dc.publisherCambridge University Press. The Journal's web site is located at http://journals.cambridge.org/action/displayJournal?jid=ECT-
dc.relation.ispartofEconometric Theory-
dc.rightsEconometric Theory. Copyright © Cambridge University Press.-
dc.rightsThis article has been published in a revised form in Econometric Theory [http://doi.org/10.1017/S0266466619000343]. This version is free to view and download for private research and study only. Not for re-distribution, re-sale or use in derivative works. © Cambridge University Press-
dc.titleA NEW MULTILEVEL MODELING APPROACH FOR CLUSTERED SURVIVAL DATA-
dc.typeArticle-
dc.identifier.emailXu, J: xujf@hku.hk-
dc.identifier.authorityXu, J=rp02086-
dc.description.naturepostprint-
dc.identifier.doi10.1017/S0266466619000343-
dc.identifier.scopuseid_2-s2.0-85082526748-
dc.identifier.hkuros309473-
dc.identifier.volume36-
dc.identifier.issue4-
dc.identifier.spage707-
dc.identifier.epage750-
dc.identifier.isiWOS:000550217200005-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0266-4666-

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