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STATISTICS
Year : 2016  |  Volume : 7  |  Issue : 2  |  Page : 106-107

Common pitfalls in statistical analysis: The perils of multiple testing


1 Department of Anaesthesiology, Tata Memorial Centre, Mumbai, Maharashtra, India
2 Department of Surgical Oncology, Division of Thoracic Surgery, Tata Memorial Centre, Mumbai, Maharashtra, India
3 International Drug Development Institute, San Francisco, California, USA; Department of Biostatistics, Hasselt University, Hasselt, Belgium

Correspondence Address:
Priya Ranganathan
Department of Anaesthesiology, Tata Memorial Centre, Ernest Borges Road, Parel, Mumbai - 400 012, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2229-3485.179436

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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.


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