1. Introduction


    1. Referencing
  2. User Guide
  3. Theory
  4. FAQ

Important note: this wiki is a work in progress.

swe is a tool for the analysis of longitudinal and repeated measures neuroimaging data based on the sandwich estimator.

swe fits a simple "marginal model" with no need for per-subject dummy variables, and instead of iterative computation of variance components it uses the non-iterative "sandwich estimator" to find standard errors.


Guillaume, B., Hua, X., Thompson, P. M., Waldorp, L., & Nichols, T. E. (2014). Fast and accurate modelling of longitudinal and repeated measures neuroimaging data. NeuroImage, 94, 287–302. doi:10.1016/j.neuroimage.2014.03.029

Guillaume, B., Nichols, T. E. (2015). Non-parametric Inference for Longitudinal and Repeated-Measures Neuroimaging Data with the Wild Bootstrap. Poster presented at the Organization for Human Brain Mapping (OHBM) in Hawaii, 14-18, 2015. PDF.

Guillaume, B. (2015). Accurate Non-Iterative Modelling and Inference of Longitudinal Neuroimaging Data. Thesis, Maastricht University / University of Liège. PDF.

CategoryStatistics CategorySwe


Swe (last edited 15:23:42 09-10-2019 by BryanGuillaume)