Journal
TRENDS IN BIOTECHNOLOGY
Volume 36, Issue 5, Pages 488-498Publisher
CELL PRESS
DOI: 10.1016/j.tibtech.2018.01.013
Keywords
-
Categories
Ask authors/readers for more resources
The Anna Karenina effect is a manifestation of the theory-practice gap that exists when theoretical statistics are applied on real-world data. In the course of analyzing biological data for differential features such as genes or proteins, it derives from the situation where the null hypothesis is rejected for extraneous reasons (or confounders), rather than because the alternative hypothesis is relevant to the disease phenotype. The mechanics of applying statistical tests therefore must address and resolve confounders. It is inadequate to simply rely on manipulating the P-value. We discuss three mechanistic elements (hypothesis statement construction, null distribution appropriateness, and test-statistic construction) and suggest how they can be designed to foil the Anna Karenina effect to select phenotypically relevant biological features.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available