Online Program Home
  My Program

All Times EDT

Abstract Details

Activity Number: 445 - Complex Hypothesis Testing for Spatial, Functional and Neuroimaging Data
Type: Topic Contributed
Date/Time: Thursday, August 6, 2020 : 10:00 AM to 11:50 AM
Sponsor: ENAR
Abstract #313264
Title: Distribution-Free Pointwise Adjusted P-Values for Functional Hypotheses
Author(s): Philip Reiss* and Meng Xu
Companies: University of Haifa and University of Haifa
Keywords: envelope test; p-value adjustment; functional data analysis; multiple testing; permutation test; magnetic resonance imaging

Graphical tests assess whether a function of interest departs from an envelope of functions generated under a simulated null distribution. This approach originated in spatial statistics, but has recently gained some popularity in functional data analysis. Whereas such envelope tests examine deviation from a functional null distribution in an omnibus sense, in some applications we wish to do more: to obtain p-values at each point in the function domain, adjusted to control the family-wise error rate. Here we derive pointwise adjusted p-values based on envelope tests, and relate these to previous approaches for functional data under distributional assumptions. We then present two alternative distribution-free p-value adjustments that offer greater power. The methods are illustrated with an analysis of age-varying sex effects on cortical thickness in the human brain.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2020 program