How to Model Ambulatory Assessments Measured at Different Frequencies: An N = 1 Approach.

Area of Science:

• Psychology
• Behavioral Science
• Data Analysis

Background:

• Ambulatory assessment is popular for studying daily experiences and behaviors.
• Investigating dynamic relations between variables measured at different frequencies presents a challenge.
• Examples include sleep patterns (daily) and emotional states (momentary).

Purpose of the Study:

• To propose and evaluate N=1 models for analyzing dynamic relations between variables measured at different frequencies.
• To address the challenge of integrating data from varying measurement schedules in ambulatory assessment.
• To provide researchers with flexible modeling tools for understanding complex daily dynamics.

Main Methods:

• Development of two N=1 models: one focusing on day-to-day dynamics, the other on occasion-to-occasion dynamics.
• Introduction of a combined model integrating both temporal perspectives.
• Validation of model accuracy through a simulation study.
• Application to an empirical example of daily sleep quality and momentary self-doubt.

Main Results:

• The proposed models accurately capture dynamic relations between variables with different measurement frequencies.
• An empirical example demonstrated significant dynamic relationships between sleep quality and self-doubt at both momentary and daily levels.
• The models can differentiate between day-to-day and occasion-to-occasion influences.

Conclusions:

• The developed N=1 models offer a powerful approach to analyzing complex temporal dynamics in ambulatory assessment data.
• Researchers can adapt these models to fit specific theories and research questions involving multi-frequency data.
• This work enhances the understanding of how daily and momentary factors interact in everyday life.