title: Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach.
abstract: The most commonly used method in evolutionary biology for combining information across multiple tests of the same null hypothesis is Fisher's combined probability test. This note shows that an alternative method called the weighted Z-test has more power and more precision than does Fisher's test. Furthermore, in contrast to some statements in the literature, the weighted Z-method is superior to the unweighted Z-transform approach. The results in this note show that, when combining P-values from multiple tests of the same hypothesis, the weighted Z-method should be preferred.
authors.affiliation: Department of Zoology, University of British Columbia, Vancouver, BC, Canada. whitlock@zoology.ubc.ca
authors.forename: M C
authors.initials: MC
authors.lastname: Whitlock
mesh_terms: D005075:Biological Evolution; D003198:Computer Simulation; D008962:Models, Theoretical; D011336:Probability; D012107:Research Design