Date of Award
4-1982
Degree Name
Master of Arts
Department
Psychology
First Advisor
Dr. Bradley E. Huitema
Second Advisor
Dr. Dale Brethower
Third Advisor
Dr. R. Wayne Fuqua
Access Setting
Masters Thesis-Open Access
Abstract
Many methodologists have asserted that serial dependency is a common data characteristic of research employing single subject responses measured over time. This dependency, when present, invalidates usage of most conventional data analysis techniques and may necessitate use of Auto-Regressive Integrated Moving Average (ARIMA) models which accommodate serial dependency characteristics of those data. Results indicate that minimal levels of serial dependency are present in most areas, yet is higher in areas which sample behaviors at very long or short time intervals and the dependent data usually show linear trend or cycle. A review shows that once trends and cycles are accounted for, serial dependency is very uncommon. The results indicate that serial dependency is not as prevalent as many researchers have assumed it to be and the need for widespread use of ARIMA models in operant research is limited.
Recommended Citation
Anderson, Robert James, "Autocorrelation in Behavioral Time-Series Data: The Search Goes On" (1982). Masters Theses. 1640.
https://scholarworks.wmich.edu/masters_theses/1640