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Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Assessment of selective mutism (SM) is hampered by the lack of diagnostic measures. The Frankfurt Scale of Selective Mutism was developed for kindergarteners, schoolchildren, and adolescents, including the diagnostic scale (DS) and the severity scale (SS). The objective of this study was to evaluate this novel, parent-rated questionnaire among individuals aged 3 to 18 years (n = 334) with SM, social phobia, internalizing disorders, and a control group. Item analysis resulted in high item-total correlations, and internal consistency in both scales was excellent with Cronbach’s α = .90-.98. Exploratory factor analysis of the SS consistently yielded a one-factor solution. Mean sum scores of the DS differed significantly between the diagnostic groups, and the receiver operating characteristic analysis resulted in optimal cutoffs for distinguishing SM from all other groups with the area under the curves of 0.94-1.00. The SS sum scores correlated significantly with SM’s clinician-rated symptom severity.