title: Accurate statistical tests for smooth classification images.
abstract: Despite an obvious demand for a variety of statistical tests adapted to classification images, few have been proposed. We argue that two statistical tests based on random field theory (RFT) satisfy this need for smooth classification images. We illustrate these tests on classification images representative of the literature from F. Gosselin and P. G. Schyns (2001) and from A. B. Sekuler, C. M. Gaspar, J. M. Gold, and P. J. Bennett (2004). The necessary computations are performed using the Stat4Ci Matlab toolbox.
authors.affiliation: Département de Psychologie, Université de Montréal, Montréal, QC, Canada. alan.chauvin@univ-lille3.fr
authors.forename: Alan
authors.initials: A
authors.lastname: Chauvin
authors.forename: Keith J
authors.initials: KJ
authors.lastname: Worsley
authors.forename: Philippe G
authors.initials: PG
authors.lastname: Schyns
authors.forename: Martin
authors.initials: M
authors.lastname: Arguin
authors.forename: Frédéric
authors.initials: F
authors.lastname: Gosselin
mesh_terms: D002965:Classification; D003952:Diagnostic Imaging; D006801:Humans; D013223:Statistics as Topic / Q000592:standards