An introduction with medical applications to functional data analysis

Stat Med. 2013 Dec 30;32(30):5222-40. doi: 10.1002/sim.5989. Epub 2013 Sep 30.


Functional data are data that can be represented by suitable functions, such as curves (potentially multi-dimensional) or surfaces. This paper gives an introduction to some basic but important techniques for the analysis of such data, and we apply the techniques to two datasets from biomedicine. One dataset is about white matter structures in the brain in multiple sclerosis patients; the other dataset is about three-dimensional vascular geometries collected for the study of cerebral aneurysms. The techniques described are smoothing, alignment, principal component analysis, and regression.

Keywords: curve alignment; functional principal component analysis; functional regression; smoothing.

Publication types

  • Review

MeSH terms

  • Data Interpretation, Statistical*
  • Humans
  • Intracranial Aneurysm / pathology
  • Magnetic Resonance Angiography
  • Magnetic Resonance Imaging
  • Multiple Sclerosis / pathology
  • Principal Component Analysis / methods*
  • Regression Analysis*