Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)



First Advisor

Wayne Velicer


Technological advances in both data acquisition and analytics have increased the usefulness and feasibility of employing idiographic methods in behavioral science research. While there are many advantages to employing an idiographic approach, one major criticism has been the lack of generalizability from single subject research to a larger population of interest. Developing a Typology of Temporal Patterns (TTP) is a novel method that can help address the issue of generalizability in idiographic research. TTP combines time series analysis and dynamic cluster analysis to form subgroups of individuals who share similar longitudinal trajectories. The present study demonstrates the usefulness of TTP by applying it to the study of cardiovascular arousal to environmental stressors in individuals with autism spectrum disorder (ASD). Secondary data analysis was conducted on heart rate data collected from 43 individuals with ASD exposed to a series of experimentally and systematically manipulated environmental stressors. Interrupted time series analysis was performed for each participant to examine individual-level heart rate patterns. The diversity observed across the interrupted time series results demonstrates a need to identify subgroups of individuals with similar heart rate patterns. Accordingly, dynamic cluster analysis was conducted on the heart rate time series data from the 43 participants. The first cluster analysis revealed a three-cluster solution (Low Cluster, Middle Cluster, and High Cluster) that was largely dominated by differences in heart rate level (or mean). A second cluster analysis, focused on shape and scatter of heart rate patterns, revealed two subgroups (Autonomic Stabiles and Autonomic Labiles) that differed in their patterns of heart rate reactivity to stressors and heart rate recovery during rest conditions. Following the cluster procedures, a series of ANOVAs showed differences between the identified subgroups on a variety of time series variables. The findings provide support for the utility of TTP to evaluate idiographic data at both individual and subgroup levels, and suggest that cardiovascular reactivity is a useful index for identifying meaningful individual differences in the prevalent and heterogeneous population of ASD.