Skip Navigation


IJE Advance Access originally published online on November 14, 2006
International Journal of Epidemiology 2006 35(6):1588-1589; doi:10.1093/ije/dyl226
This Article
Right arrow Full Text Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
35/6/1588    most recent
dyl226v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by MARSHALL, R.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by MARSHALL, R.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Published by Oxford University Press on behalf of the International Epidemiological Association © The Author 2006; all rights reserved.

Letters to the Editor

A method to automate probabilistic sensitivity analyses of misclassified binary variables

ROGER MARSHALL

Epidemiology and Biostatistics, School of Population Health, University of Auckland, New Zealand. E-mail: rj.marshall@auckland.ac.nz

The first 10% of the full text of this article appears below.

Fox et al.1 examine the relationship between odds ratios for a binary measured exposure variable X and the underlying true exposure E. One form of the relationship2,3 that the authors do not consider is:

Formula 11
where Q0, Q1 (Formula 1, Formula 1) are quality indices of misclassification in cases (controls). Here Q1 is sensitivity (SE) re-scaled according the measured prevalence of exposure PX i.e. Q1 = (SE – PX. . . [Full Text of this Article]


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?