Perspectives in Clinical Research

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

Common pitfalls in statistical analysis: The perils of multiple testing


Priya Ranganathan1, CS Pramesh2, Marc Buyse3 
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

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.


How to cite this article:
Ranganathan P, Pramesh C S, Buyse M. Common pitfalls in statistical analysis: The perils of multiple testing.Perspect Clin Res 2016;7:106-107


How to cite this URL:
Ranganathan P, Pramesh C S, Buyse M. Common pitfalls in statistical analysis: The perils of multiple testing. Perspect Clin Res [serial online] 2016 [cited 2019 Dec 14 ];7:106-107
Available from: http://www.picronline.org/article.asp?issn=2229-3485;year=2016;volume=7;issue=2;spage=106;epage=107;aulast=Ranganathan;type=0