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パネルデータ回帰不連続デザイン×パネルデータ中断時系列分析×
分野因果推論因果推論
系統Regression modelRegression model
提唱年1960 (original RDD); panel extension codified 2000s–2010s2000s–2010s
提唱者Thistlethwaite & Campbell (1960); panel extension developed through Lee & Lemieux (2010) and related applied workShadish, Cook & Campbell (design framework); Bernal, Cummins & Gasparrini (epidemiological tutorial)
種類Causal inference / quasi-experimentalQuasi-experimental causal inference
原典Lee, D. S., & Lemieux, T. (2010). Regression Discontinuity Designs in Economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗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. DOI ↗
別名Panel RD, Panel RDD, Longitudinal Regression Discontinuity, Fixed-Effects RDDpanel ITS, multi-unit ITS, panel ITSA, controlled interrupted time series
関連55
概要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.
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ScholarGate手法を比較: Panel Data Regression Discontinuity Design · Panel Data Interrupted Time Series. 2026-06-18に以下より取得 https://scholargate.app/ja/compare