Time-Related Considerations for Modeling Event-Based Data Collected via Ecological Momentary Assessment

Area of Science:

• Psychology
• Behavioral Science
• Data Science

Background:

• Ecological momentary assessments (EMAs) and wearable devices enable real-time data collection on daily life events.
• Dense sampling approaches allow for rapid event measurement, expanding temporal modeling possibilities.

Purpose of the Study:

• To provide an overview of survival analysis for psychosocial and behavioral scientists.
• To describe time-based considerations for applying survival analysis to event-based EMA data.
• To illustrate the application of survival analysis with examples and spark future research.

Main Methods:

• Overview of survival analysis principles.
• Discussion of time-based considerations for EMA data.
• Illustrative examples of survival analysis applied to event data.

Main Results:

• Survival analysis offers a powerful framework for analyzing event-based EMA data.
• Specific time-based considerations are crucial for accurate modeling.
• The approach can address novel research questions in psychological and behavioral sciences.

Conclusions:

• Survival analysis is underutilized but highly relevant for EMA data.
• Understanding temporal dynamics in event data can be enhanced with survival analysis.
• This method can uncover new insights into the timing and occurrence of daily life events.