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

Autor/inn/en	Cohen, Ira L.; Liu, Xudong; Hudson, Melissa; Gillis, Jennifer; Cavalari, Rachel N. S.; Romanczyk, Raymond G.; Karmel, Bernard Z.; Gardner, Judith M.
Titel	Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis
Quelle	In: Journal of Autism and Developmental Disorders, 46 (2016) 9, S.3006-3022 (17 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0162-3257
DOI	10.1007/s10803-016-2843-0
Schlagwörter	Classification; Regression (Statistics); Children; Autism; Pervasive Developmental Disorders; Behavior Rating Scales; Accuracy; Parents; Teachers; Prediction; Data Analysis + Suchen Sie Ihr Suchwort? Classification system; Klassifikation; Klassifikationssystem; Regression; Regressionsanalyse; Child; Kind; Kinder; Autismus; Eltern; Lehrer; Lehrerin; Lehrende; Vorhersage; Auswertung
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. (As Provided).
Anmerkungen	Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01