dc.contributor.author |
Lee, Alan |
en |
dc.contributor.author |
Scott, Alastair |
en |
dc.contributor.author |
Wild, Christopher |
en |
dc.date.accessioned |
2011-11-17T17:34:35Z |
en |
dc.date.issued |
2010 |
en |
dc.identifier.citation |
Biometrika 97(2):361-374 2010 |
en |
dc.identifier.issn |
0006-3444 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/9303 |
en |
dc.description.abstract |
In this paper we discuss the analysis of multi-phase, or multi-stage, case-control studies and present an efficient semiparametric maximum-likelihood approach that unifies and extends earlier work, including the seminal case-control paper by Prentice & Pyke (1979), work by Breslow & Cain (1988), Scott & Wild (1991), Breslow & Holubkov (1997) and others. The theoretical derivations apply to arbitrary binary regression models but we present results for logistic regression and show that the approach can be implemented by including additional intercept terms in the logistic model and then making some simple corrections to the score and information equations used in a Newton–Raphson or Fisher-scoring maximization of the prospective loglikelihood. |
en |
dc.language |
EN |
en |
dc.publisher |
Oxford University Press |
en |
dc.relation.ispartofseries |
Biometrika |
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/0006-3444/ |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.subject |
Logistic regression |
en |
dc.subject |
Maximum likelihood |
en |
dc.subject |
Multi-stage sampling |
en |
dc.subject |
Response-selective sampling |
en |
dc.subject |
Semiparametric efficiency |
en |
dc.subject |
Two- and three-phase sampling |
en |
dc.subject |
NATIONAL WILMS-TUMOR |
en |
dc.subject |
MAXIMUM-LIKELIHOOD |
en |
dc.subject |
REGRESSION-MODELS |
en |
dc.subject |
LOGISTIC-REGRESSION |
en |
dc.subject |
2-PHASE |
en |
dc.subject |
DISEASE |
en |
dc.subject |
DESIGN |
en |
dc.title |
Efficient estimation in multiphase case-control studies |
en |
dc.type |
Journal Article |
en |
dc.identifier.doi |
10.1093/biomet/asq009 |
en |
pubs.issue |
2 |
en |
pubs.begin-page |
361 |
en |
pubs.volume |
97 |
en |
dc.rights.holder |
Copyright: Biometrika Trust |
en |
pubs.author-url |
http://biomet.oxfordjournals.org/content/97/2/361 |
en |
pubs.end-page |
374 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Article |
en |
pubs.elements-id |
90755 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
Statistics |
en |
dc.identifier.eissn |
1464-3510 |
en |
pubs.record-created-at-source-date |
2010-09-01 |
en |