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Combining probability from independent tests: the weighted Z ‐method is superior to Fisher's approach
Author(s) -
WHITLOCK M. C.
Publication year - 2005
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1111/j.1420-9101.2005.00917.x
Subject(s) - null hypothesis , statistics , biology , exact test , contrast (vision) , statistical hypothesis testing , multiple comparisons problem , mathematics , alternative hypothesis , artificial intelligence , computer science
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.