방법 비교

	회귀 불연속 설계의 패널 데이터 (Panel RDD)	패널 데이터 단절 시계열
분야	인과추론	인과추론
계열	Regression model	Regression model
기원 연도	1960 (original RDD); panel extension codified 2000s–2010s	2000s–2010s
창시자	Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied work	Shadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial)
유형	Causal inference / quasi-experimental	Quasi-experimental causal inference
원전	Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355.	Lopez Bernal, J., Cummins, S., & Gasparrini, A. (2017). Interrupted time series regression for the evaluation of public health interventions: a tutorial. International Journal of Epidemiology, 46(1), 348-355.
별칭	Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDD	panel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series
관련	5	5
요약	Panel data regression discontinuity design (Panel RDD) combines the sharp local identification of a regression discontinuity with the within-unit variation available in repeated-observation panel data. Units are observed across multiple periods, and treatment is assigned based on whether a running variable crosses a known threshold. By leveraging both the discontinuity and panel structure, researchers can control for unobserved unit-level heterogeneity while estimating a causal treatment effect near the threshold.	Panel Data Interrupted Time Series (panel ITS) is a quasi-experimental method that estimates the causal effect of an intervention using repeated observations from multiple units over time. By exploiting variation across both units and time periods, it provides stronger causal identification than single-unit ITS, detecting changes in the level and slope of the outcome trajectory immediately following a clearly dated intervention.