Abstract
In this issue of Pediatrics , Dr Shattuck presents findings from his intensive statistical analysis of diagnostic substitution in US special education data.1 Diagnostic substitution is one factor potentially contributing to the large observed increase in autism prevalence and, unlike many other possible factors, empirical evaluation of this factor can actually be approached by using existing administrative data. However, analyses of this sort are not without their challenges and complexities. When considering diagnostic substitution in US special education data, we are limited to group-level comparisons. We do not know whether individual children have switched classifications, and of course we can never know whether a given child in a particular birth cohort would have been classified differently had they been born either earlier or later. At best, analyses of this type are merely trying to determine if trends in one classification have the potential to offset those in another. Although Shattuck's models incorporate a number of advantageous features, they essentially distill the assessment of this … Address correspondence to Craig J. Newschaffer, PhD, Department of Epidemiology, Center for Autism and Developmental Disabilities Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Room E6030, Baltimore, MD 21205. E-mail: cnewscha{at}jhsph.edu
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