Multisite Study of New Autism Diagnostic Interview-Revised (ADI-R) Algorithms for Toddlers and Young Preschoolers.
Using two independent datasets provided by National Institute of Health funded consortia, the Collaborative Programs for Excellence in Autism and Studies to Advance Autism Research and Treatment ( n = 641) and the National Institute of Mental Health ( n = 167), diagnostic validity and factor structu...
| Published in: | Journal of Autism & Developmental Disorders Vol. 43; no. 7; pp. 1527 - 1539 |
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| Main Authors: | , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Springer Nature
Jul2013
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| Online Access: | View this record in EBSCOhost |
| Summary: | Using two independent datasets provided by National Institute of Health funded consortia, the Collaborative Programs for Excellence in Autism and Studies to Advance Autism Research and Treatment ( n = 641) and the National Institute of Mental Health ( n = 167), diagnostic validity and factor structure of the new Autism Diagnostic Interview (ADI-R) algorithms for toddlers and young preschoolers were examined as a replication of results with the 2011 Michigan sample (Kim and Lord in J Autism Dev Disord 42(1): 82-93, 2012). Sensitivities and specificities and a three-factor solution were replicated. Results suggest that the new ADI-R algorithms can be appropriately applied to existing research databases with children from 12 to 47 months and down to nonverbal mental ages of 10 months for diagnostic grouping. |
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