Comparison of Nomothetic Versus Idiographic-Oriented Methods for Making Predictions About Distal Outcomes From Time Series Data

We illustrate the idiographic/nomothetic debate by comparing 3 approaches to using daily self-report data on affect for predicting relationship quality and breakup. The 3 approaches included (a) the first day in the series of daily data; (b) the mean and variability of the daily series; and (c) parameters from dynamic factor analysis, a statistical model that uses all measurement occasions to estimate the structure and dynamics of the data. Our results indicated that data from the first measurement occasion does not provide information about the couples' relationship quality or breakup 1 to 2 years later. The mean and variability of the time series, however, were more informative: females' average positive and negative affect across time was related to relationship quality, whereas males' variability in negative affect across time was predictive of breakup. The dynamic factor analysis, in turn, allowed us to extract information central to the dyadic dynamics. This information proved useful to predict relationship quality but not breakup. The importance of examining intraindividual variability and couple dynamics is highlighted.