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Achenbach used machine learning and principal component analysis when developing the ASEBA in order to cluster symptoms together when forming the assessment's eight categories. This approach ignored the syndrome clusters found in the DSM-I, instead relying on patterns found in case records of children with identified psychopathologies.
The CBCL also has a few items that only contribute to the Total score, which were considered clinically important even though too rare to lump into the syndrome scales. The CBCL also uses a normative sample to create standard scores. These compare the raw score to what would be typical compared to responses for youths of the same gender and ...
This rudimentary computerized interpretation is not far off from the methods used today. [3] In 1969, the first program able to generate narrative reports based on scale configurations was released. [4] By 1985, it was estimated that as many as 1.5 million MMPI protocols had been interpreted by computer-based test interpretation (CBTI) programs ...
An early study of the PSC compared it with the Child Behavior Checklist (CBCL) developed by Achenbach and found kappa = 0.76 indicating a high level of agreement. [4] The original study of the PSC-17 compared its subscales to other validated parent report instruments and found good agreement.
Achenbach has authored more than 300 publications, including over 30 books, monographs, and assessment manuals. Bérubé, R.L., & Achenbach, T.M. (2015). Bibliography of published studies using the Achenbach System of Empirically Based Assessment (ASEBA). Burlington, VT: University of Vermont Research Center for Children, Youth, and Families.
The Center for Biological and Computational Learning (CBCL) BBC: Visions of the Future - February 29, 2008 - This is part of the excellent BBC series entitled "visions of the future". This short clip (3min) here shows work performed at CBCL (MIT) about a computational neuroscience model of the ventral stream of the visual cortex.
The Millon Clinical Multiaxial Inventory – Fourth Edition (MCMI-IV) is the most recent edition of the Millon Clinical Multiaxial Inventory.The MCMI is a psychological assessment tool intended to provide information on personality traits and psychopathology, including specific mental disorders outlined in the DSM-5.
the goodness of fit of the form of the percept to the form of the inkblot. Score 0=poor 1=fair, 2=good 7: Color (C) the apparent primacy of color, including black, gray and white, as a response-determinant. score 0=no use of color, 1=secondary to form, 2=primary determinant with some form present, 3=primary determinant 8: Shading (Sh)