Multivariate Null Hypothesis Testing Using Continuous ABC Recording Measures with Bayesian Statistics for Severe Problem Behaviors Across Settings: Case Report

Applied behavior analysis relies on data to identify and target behaviors, provide intervention, monitor progress, and report findings that are essential to effective behavioral intervention. Currently, null hypothesis testing through single case research designs are used by behavior analysts during service provision due to its efficacy, reliability, and validity. Although null hypothesis testing is empirically supported in behavior analytic literature, its design impedes its ability to adequately provide insight on variables that may be integral to treatment success. Contrastingly, continuous ABC recording procedures may provide experimental control within behavior analytic evidence-based principles. Continuous methods facilitate multivariate analysis of naturally occurring variables where observations within routine environments elicit operative data analysis. In conjunction with multivariable recording, Bayesian statistics offer assistive technologies for educators, interventionists, and families. Bayesian analysis alternatively provides means for addressing limitations involved in null hypothesis testing as demonstrated in a case study of an adolescent male with multiple comorbid mental health diagnoses, neurological disorders, intellectual disability, and dangerous behaviors.