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. 2016 Apr-Jun;7(2):106-7.
doi: 10.4103/2229-3485.179436.

Common pitfalls in statistical analysis: The perils of multiple testing

Priya Ranganathan  1 , C S Pramesh  2 , Marc Buyse  3
Affiliations

Common pitfalls in statistical analysis: The perils of multiple testing

Priya Ranganathan et al. Perspect Clin Res. 2016 Apr-Jun.

Abstract

Multiple testing refers to situations where a dataset is subjected to statistical testing multiple times - either at multiple time-points or through multiple subgroups or for multiple end-points. This amplifies the probability of a false-positive finding. In this article, we look at the consequences of multiple testing and explore various methods to deal with this issue.

Keywords: Biostatistics; data interpretation; multiplicity; statistical significance.

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References

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