Henrik Singmann Klaus Oberauer Alodie Rey-Mermet 2021 Attentional control refers to the ability to maintain and implement a goal and goal-relevant information when facing distraction. So far, previous research has failed to substantiate strong evidence for a psychometric construct of attentional control. This has been argued to result from two methodological shortcomings: (a) the neglect of individual differences in speed-accuracy trade-offs when only speed or accuracy is used as dependent variable, and (b) the difficulty of isolating attentional control from measurement error. To overcome both issues, we combined hierarchical-Bayesian Wiener diffusion modeling with structural equation modeling. We re-analyzed the dataset from Rey-Mermet, Gade, and Oberauer (2018), which includes data from a large set of attentional-control tasks from young and older adults. Even when accounting for speed-accuracy trade-offs and removing measurement error, measures of attentional control failed to correlate with each other and to load on a latent variable. These results emphasize the necessity of rethinking attentional control. application/pdf https://sonar.unidistance.ch/global/documents/322117 https://n2t.net/ark:/51647/srd1322117 https://sonar.unidistance.ch/documents/322117/files/Rey-Mermet et al. - 2021 - Neither measurement error nor speed-accuracy trade.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.31234/osf.io/3h26y info:eu-repo/semantics/altIdentifier/ark/51647/srd1322117 info:eu-repo/semantics/openAccess CC BY PsyArxiv. - 2021 executive functions cognitive control attentional control individual differences hierarchical-Bayesian Wiener diffusion modeling structural equation modeling Open access Open data info:eu-repo/classification/udc/159.9 Neither measurement error nor speed-accuracy trade-offs explain the difficulty of establishing attentional control as a psychometric construct: Evidence from a latent-variable analysis using diffusion modeling http://purl.org/coar/resource_type/c_816b