Abstract
The latent class structure of autism symptoms from the time of diagnosis to age 6 years was examined in a sample of 280 children with autism spectrum disorder. Factor mixture modeling was performed on 26 algorithm items from the Autism Diagnostic Interview - Revised at diagnosis (Time 1) and again at age 6 (Time 2). At Time 1, a “2-factor/3-class” model provided the best fit to the data. At Time 2, a “2-factor/2-class” model provided the best fit to the data. Longitudinal (repeated measures) analysis of variance showed that the “2-factor/3-class” model derived at the time of diagnosis allows for the identification of a subgroup of children (9 % of sample) who exhibit notable reduction in symptom severity.
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Acknowledgments
This study was supported by the Canadian Institutes of Health Research, Autism Speaks, the Government of British Columbia, the Alberta Innovates Health Solutions, and the Sinneave Family Foundation. Dr. Stelios Georgiades is supported by an Autism Research Training (ART) fellowship by the Canadian Institutes of Health Research. The authors thank all the families who participate in the Pathways in ASD study. The authors also acknowledge the members of the Pathways in ASD Study Team. Parts of this paper have been presented at the International Meeting for Autism Research (Spain, 2013). An earlier version of the paper was included as a chapter in a dissertation by Dr. Georgiades (PhD degree in Health Research Methodology, McMaster University, Ontario, Canada).
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Georgiades, S., Boyle, M., Szatmari, P. et al. Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6. J Autism Dev Disord 44, 3045–3055 (2014). https://doi.org/10.1007/s10803-014-2167-x
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DOI: https://doi.org/10.1007/s10803-014-2167-x