Modeling long-term changes in daily within-person associations: An application of multilevel SEM

Short-term within-person associations are considered to reflect unique dynamic characteristics of an individual and are frequently used to predict distal outcomes. These effects are typically examined with a 2-step statistical process. The present research demonstrates how long-term changes in short-term within-person associations can be modeled simultaneously within a multilevel structural equation modeling framework. We demonstrate the utility of this model using measurement burst data from the National Study of Daily Experiences (NSDE) embedded within the Midlife in the United States (MIDUS) longitudinal study. Two measurement bursts were separated by 9 years, with each containing daily measures of stress and affect across 8 consecutive days. Measures of life satisfaction and psychological well-being were also assessed across the 9-year period. Three-level structural equation models were fit to simultaneously model short-term within-person associations between stress and negative affect and long-term changes in these associations over the 9-year period. Individual differences in long-term changes of the short-term dynamics between stress and affect predicted well-being levels. We highlight how characterizing individuals based on the strength of their within-person associations across multiple time scales can be informative in predicting distal outcomes.