On the Semiparametric Efficiency of the Scott-Wild Estimator under Choice-Based and Two-Phase Sampling

Lee, A.

dc.contributor.author	Lee, A.	en
dc.date.accessioned	2009-06-12T00:11:31Z	en
dc.date.available	2009-06-12T00:11:31Z	en
dc.date.issued	2007	en
dc.identifier.citation	Journal of Applied Mathematics and Decision Sciences 2007 (86180), 23 pages. 2007	en
dc.identifier.issn	1173-9126	en
dc.identifier.uri	http://hdl.handle.net/2292/4333	en
dc.description	An open access copy of this article is available and complies with the copyright holder/publisher conditions.	en
dc.description.abstract	Using a projection approach, we obtain an asymptotic information bound for estimates of parameters in general regression models under choice-based and two-phase outcome-dependent sampling. The asymptotic variances of the semiparametric estimates of Scott and Wild (1997, 2001) are compared to these bounds and the estimates are found to be fully efficient.	en
dc.publisher	Hindawi Publishing Corporation	en
dc.relation.ispartofseries	Journal of Applied Mathematics and Decision Sciences	en
dc.rights	Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from http://www.sherpa.ac.uk/romeo/issn/1173-9126/	en
dc.rights.uri	https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm	en
dc.rights.uri	http://creativecommons.org/licenses/by/3.0/	en
dc.title	On the Semiparametric Efficiency of the Scott-Wild Estimator under Choice-Based and Two-Phase Sampling	en
dc.type	Journal Article	en
dc.subject.marsden	Fields of Research::230000 Mathematical Sciences::230100 Mathematics	en
dc.identifier.doi	10.1155/2007/86180	en
pubs.issue	86180	en
pubs.begin-page	23 pages	en
pubs.volume	2007	en
dc.description.version	VoR - Version of Record	en
dc.rights.holder	Copyright: Hindawi Publishing Corporation	en
dc.rights.accessrights	http://purl.org/eprint/accessRights/OpenAccess	en