Abstract
We offer an introduction to the five papers that make up this special section. These papers deal with a range of the methodological challenges that face researchers analyzing fMRI data-the spatial, multilevel, and longitudinal nature of the data, the sources of noise, and so on. The papers all provide analyses of data collected by a multi-site consortium, the Function Biomedical Informatics Research Network. Due to the sheer volume of data, univariate procedures are often applied, which leads to a multiple comparisons problem (since the data are necessarily multivariate). The papers in this section include interesting applications, such as a state-space model applied to these data, and conclude with a reflection on basic measurement problems in fMRI. All in all, they provide a good overview of the challenges that fMRI data present to the standard psychometric toolbox, but also to the opportunities they offer for new psychometric modeling. © 2013 The Psychometric Society.
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Maydeu-Olivares, A., & Brown, G. (2013, April 1). Modeling fMRI Data: Challenges and Opportunities. Psychometrika. Springer Science and Business Media, LLC. https://doi.org/10.1007/s11336-013-9332-6
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