Estimation of the number of "true" null hypotheses in multivariate analysis of neuroimaging data.
The repeated testing of a null univariate hypothesis in each of many sites (either regions of interest or voxels) is a common approach to the statistical analysis of brain functional images. Procedures, such as the Bonferroni, are available to maintain the Type I error of the set of tests at a specified level. An initial assumption of these methods is a "global null hypothesis," i.e., the statistics computed on each site are assumed to be generated by null distributions. This framework may be too conservative when a significant proportion of the sites is affected by the experimental manipulation. This report presents the development of a rigorous statistical procedure for use with a previously reported graphical method, the P plot, for estimation of the number of "true" null hypotheses in the set. This estimate can then be used to sharpen existing multiple comparison procedures. Performance of the P plot method in the multiple comparison problem is investigated in simulation studies and in the analysis of autoradiographic data.
Turkheimer
F E
FE
Laboratory of Cerebral Metabolism, National Institute of Mental Health, Bethesda, Maryland 20892, USA.
Smith
C B
CB
Schmidt
K
K
D000768:Anesthesia, General; D000818:Animals; D016477:Artifacts; D001345:Autoradiography; D001786:Blood Glucose / Q000378:metabolism; D001921:Brain / Q000000981:diagnostic imaging* / Q000187:drug effects / Q000502:physiology; D001931:Brain Mapping; D003196:Computer Graphics; D003198:Computer Simulation; D003975:Diazepam / Q000494:pharmacology; D004734:Energy Metabolism / Q000187:drug effects / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007649:Ketamine / Q000494:pharmacology; D008432:Mathematical Computing; D009010:Monte Carlo Method; D051381:Rats; D014055:Tomography, Emission-Computed
D001786:Blood Glucose; D007649:Ketamine; D003975:Diazepam