dc.contributor.author |
Jiang, Yannan |
en |
dc.contributor.author |
Scott, Alastair |
en |
dc.contributor.author |
Wild, Christopher |
en |
dc.date.accessioned |
2011-11-17T17:35:52Z |
en |
dc.date.issued |
2009-01-30 |
en |
dc.identifier.citation |
Statistics in Medicine 28(2):194-204 30 Jan 2009 |
en |
dc.identifier.issn |
0277-6715 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/9310 |
en |
dc.description.abstract |
It is not uncommon for a continuous outcome variable Y to be dichotomized and analysed using logistic regression. Moser and Coombs (Statist. Med. 2004 23:1843-1860) provide a method for converting the output from a standard linear regression analysis using the original continuous outcome Y to give much more efficient inferences about the same odds-ratio parameters being estimated by the logistic regression. However, these results apply only to prospective studies. This paper follows up Moser and Coombs by providing an efficient linear-model-based Solution for data collected using case-control studies. Gains in statistical efficiency of up to 240 per cent are obtained even with small to moderate odds ratios. Differences in design efficiency between case-control and prospective sampling designs are found to be much smaller, however, when linear-model-based analyses are being used than they are when logistic regression analyses are being used. Copyright (C) 2008 John Wiley & Soils, Ltd. |
en |
dc.language |
EN |
en |
dc.publisher |
JOHN WILEY & SONS LTD |
en |
dc.relation.ispartofseries |
Statistics in Medicine |
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/0277-6715/ |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.subject |
dichotomizing logistic regression |
en |
dc.subject |
case-control sampling |
en |
dc.subject |
odds ratios |
en |
dc.subject |
linear regression |
en |
dc.subject |
confidence intervals |
en |
dc.subject |
MAXIMUM-LIKELIHOOD |
en |
dc.subject |
BINARY REGRESSION |
en |
dc.subject |
MODELS |
en |
dc.subject |
FAMILY |
en |
dc.title |
Case-control analysis with a continuous outcome variable |
en |
dc.type |
Journal Article |
en |
dc.identifier.doi |
10.1002/sim.3474 |
en |
pubs.issue |
2 |
en |
pubs.begin-page |
194 |
en |
pubs.volume |
28 |
en |
dc.rights.holder |
Copyright: John Wiley & Sons, Ltd. |
en |
dc.identifier.pmid |
18991330 |
en |
pubs.end-page |
204 |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/RestrictedAccess |
en |
pubs.subtype |
Article |
en |
pubs.elements-id |
90786 |
en |
pubs.org-id |
Science |
en |
pubs.org-id |
Statistics |
en |
pubs.record-created-at-source-date |
2010-09-01 |
en |
pubs.dimensions-id |
18991330 |
en |