Are We Under-Estimating the Association Between Autism Symptoms?: The Importance of Considering Simultaneous Selection When Using Samples of Individuals Who Meet Diagnostic Criteria for an Autism Spectrum Disorder

Aja Louise Murray, Karen McKenzie, Renate Kuenssberg, Michael O’Donnell

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

Abstract

The magnitude of symptom inter-correlations in diagnosed individuals has contributed to the evidence that autism spectrum disorders (ASD) is a fractionable disorder. Such correlations may substantially under-estimate the population correlations among symptoms due to simultaneous selection on the areas of deficit required for diagnosis. Using statistical simulations of this selection mechanism, we provide estimates of the extent of this bias, given different levels of population correlation between symptoms. We then use real data to compare domain inter-correlations in the Autism Spectrum Quotient, in those with ASD versus a combined ASD and non-ASD sample. Results from both studies indicate that samples restricted to individuals with a diagnosis of ASD potentially substantially under-estimate the magnitude of association between features of ASD.
Original languageEnglish
Pages (from-to)2921-2930
JournalJournal of Autism and Developmental Disorders
Volume44
Issue number11
DOIs
Publication statusPublished - 1 Nov 2014

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