An investigation of the false discovery rate and the misinterpretation of p-values

dc.contributor.author	Colquhoun, David	en_US
dc.date.accessioned	2016-07-18T06:49:08Z
dc.date.available	2016-07-18T06:49:08Z
dc.date.issued	2014	en_US
dc.identifier.other	HPU4160433	en_US
dc.identifier.uri	https://lib.hpu.edu.vn/handle/123456789/22276
dc.description.abstract	If you use p=0.05 to suggest that you have made a discovery, you will be wrong at least 30% of the time. If, as is often the case, experiments are underpowered, you will be wrong most of the time. This conclusion is demonstrated from several points of view. First, tree diagrams which show the close analogy with the screening test problem. Similar conclusions are drawn by repeated simulations oft-tests.	en_US
dc.format.extent	16 p.	en_US
dc.format.mimetype	application/pdf
dc.language.iso	en	en_US
dc.subject	Statistics	en_US
dc.subject	Computational biology	en_US
dc.subject	Significance tests	en_US
dc.subject	Reproducibility	en_US
dc.subject	Statistics	en_US
dc.subject	False discovery rat	en_US
dc.title	An investigation of the false discovery rate and the misinterpretation of p-values	en_US
dc.type	Article	en_US
dc.size	741KB	en_US
dc.department	Education	en_US