20042432

Source:http://linkedlifedata.com/resource/pubmed/id/20042432

Download in:

Switch to

Custom View

Named Graph Language Inference

Statements in which the resource exists as a subject.
Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0205557, umls-concept:C0679575, umls-concept:C2587213
pubmed:issue	4
pubmed:dateCreated	2009-12-31
pubmed:abstractText	An incredible amount of data is generated in the course of a functional neuroimaging experiment. The quantity of data gives us improved temporal and spatial resolution with which to evaluate our results. It also creates a staggering multiple testing problem. A number of methods have been created that address the multiple testing problem in neuroimaging in a principled fashion. These methods place limits on either the familywise error rate (FWER) or the false discovery rate (FDR) of the results. These principled approaches are well established in the literature and are known to properly limit the amount of false positives across the whole brain. However, a minority of papers are still published every month using methods that are improperly corrected for the number of tests conducted. These latter methods place limits on the voxelwise probability of a false positive and yield no information on the global rate of false positives in the results. In this commentary, we argue in favor of a principled approach to the multiple testing problem--one that places appropriate limits on the rate of false positives across the whole brain gives readers the information they need to properly evaluate the results.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/101288795
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Dec
pubmed:issn	1749-5024
pubmed:author	pubmed-author:BennettCraig MCM, pubmed-author:MillerMichael BMB, pubmed-author:WolfordGeorge LGL
pubmed:issnType	Electronic
pubmed:volume	4
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	417-22
pubmed:dateRevised	2011-3-3
pubmed:meshHeading	pubmed-meshheading:20042432-Brain, pubmed-meshheading:20042432-Brain Mapping, pubmed-meshheading:20042432-Data Interpretation, Statistical, pubmed-meshheading:20042432-False Positive Reactions, pubmed-meshheading:20042432-Humans, pubmed-meshheading:20042432-Magnetic Resonance Imaging
pubmed:year	2009
pubmed:articleTitle	The principled control of false positives in neuroimaging.
pubmed:affiliation	Department of Psychology, University of California, Santa Barbara, Santa Barbara, CA 93106, USA. bennett@psych.ucsb.edu
pubmed:publicationType	Journal Article, Research Support, U.S. Gov't, Non-P.H.S.