Defining Autism Subgroups: A Taxometric Solution
The purpose of the present study was to determine which behavioral and physical phenotypes would be most likely to divide the ASD population into discrete subgroups. The taxometric methods of Maximum Covariance (MAXCOV) and Minus Mean Below A Cut (MAMBAC) were employed to test for categorical versus continuous variation of each phenotype across the ASD population. Data was retrieved from the Autism Genetic Resource Exchange and the University of Missouri Autism Database. The results of our analyses support subgrouping subjects based on variation in social interaction/communication, intelligence, and essential/complex phenotype; in contrast, subjects varied continuously in insistence on sameness, repetitive sensory motor actions, language acquisition, and, tentatively, adaptive functioning. Stratifying ASD samples based on taxometric results should increase power in gene-finding studies and aid in treatment efficacy research.
KeywordsAutism subgroups Taxometrics
- AGRE (n.d.). AGRE affected status categories. Retrieved 30 July 2007, from http://www.agre.org/agrecatalog/algorithm.cfm.
- American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Text revised ed. Washington, DC.Google Scholar
- Pearson Assessments. (n.d.). PPVT-III:peabody picture vocabulary test-third edition. Retrieved 30 July 2007, from http://www.ags.pearsonassessments.com/group.asp?nGroupInfoID=a12010.
- Raven, J., Raven, J. C., & Court, J. H. (1998). Manual for Raven’s progressive matrices and vocabulary scales. San Antonio: Harcourt Assessment.Google Scholar
- Ruscio, J., Haslam, N., & Ruscio, A. M. (2006). Introduction to the taxometric method (1st ed.). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar