1. Trials and tribulations of statistical significance in biochemistry and omics.
- Author
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Montero, Olimpio, Hedeland, Mikael, and Balgoma, David
- Subjects
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STATISTICAL significance , *INFERENTIAL statistics , *STATISTICAL hypothesis testing , *BIOCHEMISTRY , *FISHER exact test , *STATISTICIANS , *STATISTICS - Abstract
The use of statistical significance is under discussion. Many statisticians and researchers advocate for its retirement. Conversely, other statisticians and researchers think that its retirement would damage science. There is room for improvement in the use of hypothesis testing and p -values in biochemical sciences and omics. The selection of variables by statistical significance with solid cutoffs drives and may bias the biological interpretation of biochemical data. To obtain robust knowledge by comparing studies, it is essential to report thoroughly all results (both quantitative and categorical variables). Because of the big number of variables, the problems of selecting variables by statistical significance increase for omic studies. Over recent years many statisticians and researchers have highlighted that statistical inference would benefit from a better use and understanding of hypothesis testing, p -values, and statistical significance. We highlight three recommendations in the context of biochemical sciences. First recommendation: to improve the biological interpretation of biochemical data, do not use p -values (or similar test statistics) as thresholded values to select biomolecules. Second recommendation: to improve comparison among studies and to achieve robust knowledge, perform complete reporting of data. Third recommendation: statistical analyses should be reported completely with exact numbers (not as asterisks or inequalities). Owing to the high number of variables, a better use of statistics is of special importance in omic studies. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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