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Alzheimer's disease (AD) affects neurological, cognitive, and behavioral processes. Thus, to accurately assess this disease, researchers and clinicians need to combine and incorporate data across these domains. This presents not only distinct methodological and statistical challenges but also unique opportunities for the development and advancement of psychometric techniques. In this article, we describe relatively recent research using item response theory (IRT) that has been used to make progress in assessing the disease across its various symptomatic and pathological manifestations. We focus on applications of IRT to improve scoring, test development (including cross-validation and adaptation), and linking and calibration. We conclude by describing potential future multidimensional applications of IRT techniques that may improve the precision with which AD is measured.
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Balsis et al. (2017) studied this question.
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