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Journal of Autism and Developmental Disorders

Gepubliceerd in:

18-06-2016 | Original Paper

Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis

Auteurs: Ira L. Cohen, Xudong Liu, Melissa Hudson, Jennifer Gillis, Rachel N. S. Cavalari, Raymond G. Romanczyk, Bernard Z. Karmel, Judith M. Gardner

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 9/2016

Abstract

In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80 %, generalized to an independent validation set, and generalized across age groups and sites, and agreed well with ADOS classifications. Parent PDDBIs yielded better results than teacher PDDBIs but, when CART predictions agreed across informants, sensitivity increased. Results also revealed three subtypes of ASD: minimally verbal, verbal, and atypical; and two, relatively common subtypes of non-ASD children: social pragmatic problems and good social skills. These subgroups corresponded to differences in behavior profiles and associated bio-medical findings.

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Titel: Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis
Auteurs: Ira L. Cohen
Xudong Liu
Melissa Hudson
Jennifer Gillis
Rachel N. S. Cavalari
Raymond G. Romanczyk
Bernard Z. Karmel
Judith M. Gardner
Publicatiedatum: 18-06-2016
Uitgeverij: Springer US
Gepubliceerd in: Journal of Autism and Developmental Disorders / Uitgave 9/2016
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI: https://doi.org/10.1007/s10803-016-2843-0

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