Using Interpolated Curves to Represent and Compare Life Course Patterns
Joy Pixley, University of California, Irvine
I describe a method utilizing interpolated curves to systematically compare life course patterns. This technique preserves not only the timing and ordering of events, but also a single value associated with each event, such as severity, amount, or extent. Also, it can be utilized with events which are measured in continuous time, rather than requiring data to be coded into intervals. I demonstrate the technique using patterns of dual-earner couples' migration decisions over time. Couples are compared on the overall patterns of these events, including the extent to which each migration decision benefited one spouse's career more than that of the other spouse. Difference scores enable couples to be grouped into clusters based on similarity of overall patterns. Finally, I discuss variations on the technique that could be applied to other series of discrete, valued events, such as changes in employment, physical or mental health, or parity.
Presented in Poster Session 7