This study used confirmatory factor analysis (CFA) to determine the best model for Oppositional Defiant Disorder (ODD) symptoms in children aged 3 to 15 years, as presented in the Disruptive Behavior Rating Scale. Teachers’ ratings of the ODD symptoms of 213 children from general community schools in Australia were obtained. The findings provided most support for a bifactor model based on Stringaris and Goodman’s  three-factor model (primary factors for irritable, hurtful, and headstrong). The general factor, but not the group factors in the model, showed high omega hierarchical and explained common variance. Thus, only the general factor in this model can be meaningfully interpreted. Also, the general factor was supported with regard to external validity. Specifically, this factor, but not the group factors, correlated strongly with ADHD inattention and hyperactivity/impulsivity symptom groups, and other measures of behavioural and emotional problems. The taxonomic, diagnostic, practical, and research implications of the findings are discussed.
Oppositional defiant disorder Confirmatory factor analysis Community sample Teacher ratings, bifactor model
This is a preview of subscription content, log in to check access.
Rapson Gomez planning, design and then writing up. Vasileios Stavropoulos literature review, and writing up. George Van Doorn literature review, and writing up.
Role of Funding Source
The study was not funded by any source.
Compliance with Ethical Standards
Conflict of Interest
Authors have no current financial or other interest with any organization currently or in future in terms of the research.
All procedures followed for the present study were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all participants for being included in the study. No identifying information is included in this article. No animal or human studies were carried out by the authors for this article.
American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association; 2013.Google Scholar
American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.Google Scholar
American Psychiatric Association. Diagnostic and statistical manual. 4th ed. Text Revision (DSM-IV-TR). Washington, DC: American Psychiatric Association; 2000.Google Scholar
Krieger FV, Polanczyk GV, Goodman R, Rohde LA, Graeff-Martins AS, Salum G, et al. Dimensions of oppositionality in a Brazilian community sample: testing the DSM-5 proposal and etiological links. Journal of the American Academy of Child & Adolescent Psychiatry. 2013;52(4):389–400. doi:10.1016/j.jaac.2013.01.004.CrossRefGoogle Scholar
Aebi M, Muller UC, Asherson P, Banaschewski T, Buitelaar J, Ebstein R, et al. Predictability of oppositional defiant disorder and symptom dimensions in children and adolescents with ADHD combined type. Psychol Med. 2010;40(12):2089–100. doi:10.1017/S0033291710000590.CrossRefPubMedGoogle Scholar
Burke JD, Waldman I, Lahey BB. Predictive validity of childhood oppositional defiant disorder and conduct disorder: implications for the DSM-V. J Abnorm Psychol. 2010;119(4):739–51. doi:10.1037/a0019708.CrossRefPubMedGoogle Scholar
Burke JD, Boylan K, Rowe R, Duku E, Stepp SD, Hipwell AE, et al. Identifying the irritability dimension of ODD: application of a modified bifactor model across five large community samples of children. J Abnorm Psychol. 2014;123(4):841–51.CrossRefPubMedPubMedCentralGoogle Scholar
Rhemtulla M, Brosseau-Liard PÉ, Savalei V. When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychol Methods. 2012;17(3):354. doi:10.1037/a0029315.CrossRefPubMedGoogle Scholar
Zinbarg RE, Yovel I, Revelle W, McDonald RP. Estimating generalizability to a latent variable common to all of a scale's indicators: a comparison of estimators for ωh. Appl Psychol Meas. 2006;30(2):121–44.CrossRefGoogle Scholar
Bonifay WE, Reise SP, Scheines R, Meijer RR. When are multidimensional data unidimensional enough for structural equation modeling? An evaluation of the DETECT multidimensionality index. Struct Equ Model Multidiscip J. 2015;22(4):504–16. doi:10.1080/10705511.2014.938596.CrossRefGoogle Scholar
Hancock GR, Mueller RO. Rethinking construct reliability within latent variable systems. In: Structural equation modeling: Present and Future. 2001. pp. 195–216.Google Scholar
Zinbarg RE, Revelle W, Yovel I, Li W. Cronbach’s α, Revelle’s β, and McDonald’s ω H: their relations with each other and two alternative conceptualizations of reliability. Psychometrika. 2005;70(1):123–33. doi:10.1007/s11336-003-0974-7.CrossRefGoogle Scholar