Measuring Discontinuity in Binary Longitudinal Data

Life course perspectives focus on the variation in trajectories, generally to identify differences in variation dynamics and classify trajectories accordingly. Our goal here is to develop methods to gauge the discontinuity characteristics trajectories exhibit and demonstrate how these measures facilitate analyses aimed to evaluate, compare, aggregate, and classify behaviors based on the event discontinuity they manifest. We restrict ourselves here to binary event sequences, providing directions for extending the methods in future research. We illustrate our techniques to data on older drug users. It should be noted though that the application of these techniques is not restricted to drug use, but can be applied to a wide range of trajectory types. We suggest that the innovative measures of discontinuity presented can be further developed to provide additional analytical tools in social science research and in future applications. Our novel discontinuity measure visualizations have the potential to be valuable assessment strategies for interventions, prevention efforts, and other social services utilizing life course data.

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