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

Abstract

Ambulatory assessment has gained widespread popularity among researchers who study the dynamics of everyday experiences and behaviors, such as sleep patterns or emotional states. In this paper, we focus on the challenge that arises when we want to investigate the dynamic relations between variables measured at different frequencies. As a running example, we use a sleep quality variable measured once every morning and a momentary experience variable measured multiple times during the day for multiple days. We propose two N = 1 models that imply different processes; the first focuses on dynamic relations from day to day between sleep quality and a daily factor of the momentary experience variable, and the second focuses on dynamic relations from one measurement occasion to the next, which prioritizes when the variables affect each other. Additionally, we introduce a combination of these two models and demonstrate their accuracy with a simulation study. An empirical N = 1 example of daily sleep quality and momentary self-doubt demonstrates that dynamic relations exist between sleep quality and self-doubt at certain moments in the day and the daily factor of self-doubt. Researchers may adjust the proposed dynamic models to align with their own theories and to accommodate different data or research interests.