Combining Significance of Correlated Statistics with Application to Panel Data
The inverse normal method, which is used to combine "P"-values from a series of statistical tests, requires independence of single test statistics in order to obtain asymptotic normality of the joint test statistic. The paper discusses the modification by Hartung (1999, "Biometrical Journal", Vol. 41, pp. 849-855) , which is designed to allow for a certain correlation matrix of the transformed "P"-values. First, the modified inverse normal method is shown here to be valid with more general correlation matrices. Secondly, a necessary and sufficient condition for (asymptotic) normality is provided, using the copula approach. Thirdly, applications to panels of cross-correlated time series, stationary as well as integrated, are considered. The behaviour of the modified inverse normal method is quantified by means of Monte Carlo experiments. Copyright 2006 Blackwell Publishing Ltd.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 68 (2006)
Issue (Month): 5 (October)
|Contact details of provider:|| Postal: |
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0305-9049
More information through EDIRC
|Order Information:||Web: http://www.blackwellpublishing.com/subs.asp?ref=0305-9049|
When requesting a correction, please mention this item's handle: RePEc:bla:obuest:v:68:y:2006:i:5:p:647-663. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.