4.29 Exercise: Treatments/outcome as trajectories

  • Both treatment and outcome are measured at t = 32 (gray polygon). Outcome scale is omitted.
    • Q: What would the data look like? How many rows/variables?
    • Q: What conclusions would we draw from those measurements on the effect of university (0/1) on income (0-3000)?
    • Q: Why is that conclusion problematic?
    • Q: What considerations does the graph trigger if we extrapolate this problem to a larger population?

4.29.1 Lessons

  • Lessons to be learned
    1. Ideally, we know the timing of when units moved from control to treatment as well as when the outcome changed.