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تحلیل سری زمانی مقطع‌دار (ITS)×طرح گسستگی رگرسیون (RDD)×
حوزهاستنتاج علّیاستنتاج علّی
خانوادهRegression modelRegression model
سال پیدایش20022008
پدیدآورWagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
نوعQuasi-experimental segmented regressionQuasi-experimental causal design
منبع بنیادینBernal, J. L., 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 ↗Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗
نام‌های دیگرITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) AnaliziRDD, regression discontinuity design, sharp RDD, fuzzy RDD
مرتبط55
خلاصهInterrupted Time Series analysis is a quasi-experimental design that estimates the effect of a single, well-dated intervention by comparing the trajectory of an outcome before and after it occurs. Formalised as segmented regression by Wagner and colleagues (2002) and popularised as a public-health evaluation tutorial by Bernal, Cummins and Gasparrini (2017), it separates the intervention's impact into a change in level and a change in slope.Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.
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ScholarGateمقایسهٔ روش‌ها: Interrupted Time Series · Regression Discontinuity. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare