Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2013 Jun 30;212(3):167-74.
doi: 10.1016/j.pscychresns.2013.01.009. Epub 2013 May 1.

An application of item response theory to fMRI data: prospects and pitfalls

Michael L Thomas  1 , Gregory G Brown, Wesley K Thompson, James Voyvodic, Douglas N Greve, Jessica A Turner, Daniel H Mathalon, Judith Ford, Cynthia G Wible, Steven G Potkin; FBIRN
Affiliations

An application of item response theory to fMRI data: prospects and pitfalls

Michael L Thomas et al. Psychiatry Res. .

Abstract

When using functional brain imaging to study neuropsychiatric patients an important challenge is determining whether the imaging task assesses individual differences with equal precision in healthy control and impaired patient groups. Classical test theory (CTT) requires separate reliability studies of patients and controls to determine equivalent measurement precision with additional studies to determine measurement precision for different levels of disease severity. Unlike CTT, item response theory (IRT) provides estimates of measurement error for different levels of ability, without the need for separate studies, and can determine if different tests are equivalently difficult when investigating differential deficits between groups. To determine the potential value of IRT in functional brain imaging, IRT was applied to behavioral data obtained during a multi-center functional MRI (fMRI) study of working memory (WM). Average item difficulty was approximately one standard deviation below the ability scale mean, supporting the task's sensitivity to individual differences within the ability range of patients with WM impairment, but not within the range of most controls. The correlation of IRT estimated ability with fMRI activation during the task recognition period supported the linkage of the latent IRT scale to brain activation data. IRT can meaningfully contribute to the design of fMRI tasks.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Panels on the left are derived from acquired study data. The remaining panels are simulated data. Top: Loess fit of histograms for Working Memory Task ability (solid lines) and item difficulty (dashed lines) parameter estimates for Model 4. X-axis is scaled in standard deviation units. Bottom: standard error function for Working Memory Task ability parameter estimates in Model 4. Plots are shown for 256 easy items (left column), 171 easy items (center column), and 171 hard items (right column).
Fig. 2
Fig. 2
(A) Voxel-wise correlations of θ with %signal change during the recognition period. (B) Voxel-wise correlations of %correct with %signal change during the recognition period. Data are presented for gray matter voxels where %signal change was greater than zero.
See this image and copyright information in PMC

References

    1. Baker FB, Kim S-H. Item Response Theory: Parameter Estimation Techniques. second ed. New York: Dekker; 2004.
    1. Batchelder WH. Cognitive psychometrics: using multinomial processing tree models as measurement tools. In: Embretson SE, editor. Measuring Psychological Constructs: Advances in Model-Based Approaches. Washington, DC: American Psychological Association; 2010. pp. 71–93.
    1. Bedny M, Aguirre GK, Thompson-Schill SL. Item analysis in functional magnetic resonance imaging. NeuroImage. 2007;35:1093–1102. - PubMed
    1. Birnbaum A. Some latent trait models and their use in inferring an examinee’s ability. In: Lord FM, Novick MR, editors. Statistical Theories of Mental Test Scores. Oxford, England: Addison-Wesley; 1968.
    1. Brooks S, Gelman A. General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics. 1998;7:434–455.

Publication types