EconPapers    
Economics at your fingertips  
 

On the Screening of Large Numbers of Significance Tests

Man Yu Wong and D.R. Cox

Journal of Applied Statistics, 2007, vol. 34, issue 7, 779-783

Abstract: A brief review is given of procedures for the collective analysis of a large number of significance tests. A simple procedure previously supplied for isolating 'real' effects on the basis of a large number of significance tests is generalized to deal with two-sided tests and is also related more explicitly to the false discovery rate.

Keywords: False discovery rate; mixture of distributions; Bayes factor; multiple testing (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/02664760701240014 (text/html)
Access to full text is restricted to subscribers.

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: https://EconPapers.repec.org/RePEc:taf:japsta:v:34:y:2007:i:7:p:779-783

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/CJAS20

DOI: 10.1080/02664760701240014

Access Statistics for this article

Journal of Applied Statistics is currently edited by Robert Aykroyd

More articles in Journal of Applied Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:japsta:v:34:y:2007:i:7:p:779-783