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
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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.
KeywordsAutism spectrum disorder Range restriction Fractionable triad Simultaneous selection Sampling
Aja Louise Murray is supported by a studentship from The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, (http://ccace.ed.ac.uk), part of the cross council Lifelong Health and Wellbeing Initiative (G0700704/84698). Funding from the Biotechnology and Biological Sciences Research Council, Engineering and Physical Sciences Research Council, Economic and Social Science Research Council, and the Medical Research Council is gratefully acknowledged.
Conflict of interest
The authors have no conflict of interest to declare.
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