The Effect of Different Construct Operationalizations, Study Duration, and Preprocessing Choices on Power-Based Sample Size Recommendations in Intensive Longitudinal Research.

Abstract

To shed light on the dynamics of psychological processes, researchers often collect intensive longitudinal (IL) data by asking people to repeatedly report on their momentary experiences in daily life. Two important decisions when designing an IL study concern the number of persons and the number of measurement occasions to be included. These sample size decisions are ideally based on statistical power considerations. When conducting statistical power analysis, it is necessary to provide the value of the effect size of interest as well as of all other model parameters. In IL research, these values have to be based on previous studies. This implies that these values are subject to large heterogeneity due to differences in study design and preprocessing choices. This between-study heterogeneity can severely impact power-based sample size recommendations. In this article, we introduce an approach to investigate the impact of study design and pre-processing of previous studies and to determine a recommended sample size to account for this impact. We demonstrate how to use this approach to investigate the effect of different construct operationalizations, study duration, and preprocessing choices. This approach paves the way for more thoughtful and robust sample-size decisions.