Estimating the Biological Validity of the DSM for Attention Deficit/Hyperactivity Disorder Using Multivariate Analysis for Small Samples

Abstract

(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/126433 doi: bioRxiv preprint first posted online Apr. 11, 2017; Dimitri M. Abramov, 2 parameters were grouped by hierarchical clustering and integrated in 2 to 6 resultant vectors (RVs), from clusters at hierarchical levels 1 to 5. These RVs were used for the reclassification of subjects using the k-means method. Regarding DSM-IV-TR diagnostics, the RVs from behavioral and psychological data and ERPs from the midfrontal, mid-parietal plus right frontal, right central, and right temporal channels showed accuracy rates from 0.64 to 0.82 using the k-means reclassification. Among reclassifications with higher agreement (0.82), six subjects were reclassified (4 from the TD group, and 2 from the ADHD group). Assuming the reclassification of these six subjects, the estimated agreement between DSM and biological data was 84.61% with kappa index of 0.69. The results suggest biological validity and efficiency of DSM as a tool for ADHD diagnostics. AbstractAll rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

A interpretação estatística como produção de verdades: reflexões éticas

“…For example, to describe a complex system such as the brain of a child with Attention Deficit Hyperactivity Disorder (ADHD), we would need to collect hundreds of variables of different types. Imagine a database with up to 800 variables, as in Abramov and collaborators 8 : they allow up to 320,000 correlations, in addition to the 800 difference inferences between the ADHD and control groups.…”