On the optimally weighted z-test for combining probabilities from independent studies

Zhongxue Chen and Saralees Nadarajah

Computational Statistics & Data Analysis, 2014, vol. 70, issue C, 387-394

Abstract: Researchers have shown that the optimally weighted z-test, where the weights are the standardized expected difference in means, is more powerful than other methods when combining p-values from independent studies. However, in practice the effect for each independent study is usually unknown, which makes the optimally weighted z-test not applicable. A new test similar to the optimally weighted z-test, but with the effects being estimated from data, is derived. This new test is another generalized Fisher test which can be very powerful under certain situations. The new test is compared with existing methods through simulated data. Some suggestions for choosing tests to combine p-values from independent studies are given. The use of the new test is also illustrated by a real data application.

Keywords: Meta-analysis; Weighted z-test; Generalized Fisher test (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947313003204
Full text for ScienceDirect subscribers only.

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:eee:csdana:v:70:y:2014:i:c:p:387-394

DOI: 10.1016/j.csda.2013.09.005

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().