JSM 2012 Home

JSM 2012 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Online Program Home

Abstract Details

Activity Number: 541
Type: Invited
Date/Time: Wednesday, August 1, 2012 : 2:00 PM to 3:50 PM
Sponsor: ENAR
Abstract - #303529
Title: Dealing with Missing fMRI Data in Whole-Brain Analysis
Author(s): Mulugeta Gebregziabher*+ and Kenneth Vaden and Stefanie E Kuchinsky and Mark A. Eckert
Companies: MUSC and MUSC and MUSC and MUSC
Address: 135 Cannon St, Charleston, SC, , USA
Keywords: fMRI ; group analysis ; missing data ; multiple imputation ; spatial coverage ; neuroimaging methods

Functional magnetic resonance imaging(fMRI) analyses rarely include the entire brain because of missing data due to image-acquisition space limitations and susceptibility-artifact. This missing data problem is typically addressed by excluding voxels from analysis. As a result, brain regions are excluded from analysis that may be of theoretical or clinical interest and increases risk for Type-II and Type-I error. In this study, we evaluate multiple imputation(MI) that exploits the spatial nature of fMRI data assuming missing at random. Comparisons are made with simple-neighbor-imputation(SNI), regression imputation that accounts for covariates and neighborhood dependencies(RMI) and available case analysis in a general-linear-model framework. In both real and simulated data analysis, we study the extent to which these methods quantitatively(effect-size) and qualitatively(spatial-coverage) increased sensitivity of group analyses. Variance and mean estimates from RMI show less bias and it does not appear to increase false positive errors. Compared to omitting of voxels, RMI shows increased brain-coverage, increased size and number of significant clusters.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2012 program

2012 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.