EconPapers    
Economics at your fingertips  
 

A Small Sample Correction for Estimating Attributable Risk in Case-Control Studies

Daniel B. Rubin
Additional contact information
Daniel B. Rubin: Food and Drug Administration

The International Journal of Biostatistics, 2010, vol. 6, issue 1, pages 32

Abstract:

The attributable risk, often called the population attributable risk, is in many epidemiological contexts a more relevant measure of exposure-disease association than the excess risk, relative risk, or odds ratio. When estimating attributable risk with case-control data and a rare disease, we present a simple bias correction to the standard approach, which also makes it more stable and less variable. As with analogous corrections given by Jewell (1986) for other measures of association, the adjustment often won't make a substantial difference unless the sample size is very small or point estimates are desired within fine strata, but we discuss the possible utility for applications.

Keywords: Categorical Data Analysis; Epidemiology; attributable risk; case-control studies; small sample corrections (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://www.bepress.com/cgi/viewcontent.cgi?article=1252&context=ijb (application/pdf)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:bpj:ijbist:v:6:y:2010:i:1:n:32

Ordering information: This journal article can be ordered from
http://www.degruyter.com/view/j/ijb

Access Statistics for this article

More articles in The International Journal of Biostatistics from De Gruyter
Series data maintained by Peter Golla ().

 
Page updated 2013-04-27
Handle: RePEc:bpj:ijbist:v:6:y:2010:i:1:n:32