Statistical adjustments for brain size in volumetric neuroimaging studies: some practical implications in methods

UMMS Affiliation

Department of Psychiatry; Intellectual and Developmental Disabilities Research Center

Publication Date


Document Type



Adolescent; Brain; *Brain Mapping; Child; Female; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Organ Size; Statistics as Topic


Nervous System | Neurology | Neuroscience and Neurobiology | Psychiatry


Volumetric magnetic resonance imaging (MRI) brain data provide a valuable tool for detecting structural differences associated with various neurological and psychiatric disorders. Analysis of such data, however, is not always straightforward, and complications can arise when trying to determine which brain structures are "smaller" or "larger" in light of the high degree of individual variability across the population. Several statistical methods for adjusting for individual differences in overall cranial or brain size have been used in the literature, but critical differences exist between them. Using agreement among those methods as an indication of stronger support of a hypothesis is dangerous given that each requires a different set of assumptions be met. Here we examine the theoretical underpinnings of three of these adjustment methods (proportion, residual, and analysis of covariance) and apply them to a volumetric MRI data set. These three methods used for adjusting for brain size are specific cases of a generalized approach which we propose as a recommended modeling strategy. We assess the level of agreement among methods and provide graphical tools to assist researchers in determining how they differ in the types of relationships they can unmask, and provide a useful method by which researchers may tease out important relationships in volumetric MRI data. We conclude with the recommended procedure involving the use of graphical analyses to help uncover potential relationships the ROI volumes may have with head size and give a generalized modeling strategy by which researchers can make such adjustments that include as special cases the three commonly employed methods mentioned above.

DOI of Published Version



O'Brien LM, Ziegler DA, Deutsch CK, Frazier JA, Herbert MR, Locascio JJ. Statistical adjustments for brain size in volumetric neuroimaging studies: some practical implications in methods. Psychiatry Res. 2011 Aug 30;193(2):113-22. doi: 10.1016/j.pscychresns.2011.01.007. PubMed PMID: 21684724; PubMed Central PMCID: PMC3510982. Link to article on publisher's site

Journal/Book/Conference Title

Psychiatry research

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