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Guidelines for the application of ARIMA models in time series
1Faculty of Nursing, University of Alberta, Edmonton, Canada.
Research in Nursing & Health
|December 1, 1990
Summary
Time series analysis offers a powerful method for evaluating nursing interventions by tracking changes over time. While promising for nursing research, practical and inferential challenges exist in its application.
Area of Science:
- Nursing Research
- Quantitative Methods
- Behavioral Science
Background:
- Time series analysis is a valuable, yet underutilized, method for assessing nursing interventions.
- It allows for the analysis of individual behavioral changes and future predictions.
Framework:
- Time series modeling provides a robust framework for understanding dynamic processes in nursing.
- The interrupted time series design is particularly relevant for intervention evaluation.
Implementation:
- Challenges in implementing time series analysis in nursing research include practical and inferential difficulties.
- These limitations require careful consideration during study design and data interpretation.
Implications:
- Despite challenges, time series analysis holds significant potential for advancing nursing science.
- Addressing methodological limitations can enhance the utility of time series models in clinical practice and research.
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