Analyzing the Effects of Unplanned Events on Time Series Data
Author Information
Author(s): Gilmour Stuart, Degenhardt Louisa, Hall Wayne, Day Carolyn
Primary Institution: National Drug and Alcohol Research Centre, University of New South Wales
Hypothesis
How can intervention time series analysis (ITSA) be adapted to assess the impact of unplanned events when their timing is uncertain?
Conclusion
The methods described provide valuable insights into the consequences of unplanned interventions while minimizing the risk of erroneous conclusions.
Supporting Evidence
- The study illustrates the application of ITSA using the Australian heroin shortage as a case study.
- Findings suggest that the heroin shortage led to a significant reduction in heroin possession offences.
- Data from various sources confirmed the timing and impact of the heroin shortage.
Takeaway
This study shows how to use special methods to understand what happens when something unexpected, like a sudden drop in heroin availability, occurs.
Methodology
The study uses intervention time series analysis (ITSA) to model the impact of the Australian heroin shortage on various health and social indicators.
Potential Biases
Potential biases may arise from the exploratory model-building process and the reliance on data that was not specifically collected for the study.
Limitations
The study's exploratory nature may lead to challenges in defining the onset of the event and selecting appropriate outcome indicators.
Participant Demographics
Key informants included law enforcement personnel and health professionals involved with drug users.
Digital Object Identifier (DOI)
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