Vertaile menetelmiä

	Regression discontinuity design in education research	Aikasarjojen katkosanalyysi (Interrupted Time Series, ITS)
Tieteenala	Kausaalipäättely	Kausaalipäättely
Menetelmäperhe	Regression model	Regression model
Syntyvuosi	1960 (origination); 1999-2010 (education economics canon)	2002
Kehittäjä	Thistlethwaite & Campbell (1960); popularized in education economics by Angrist & Lavy (1999), Lee & Lemieux (2010)	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
Tyyppi	Quasi-experimental causal inference	Quasi-experimental segmented regression
Alkuperäislähde	Lee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48(2), 281-355.	Bernal, 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.
Rinnakkaisnimet	RDD in education, education RD design, sharp RDD education, score-cutoff design	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Liittyvät	5	5
Tiivistelmä	Regression discontinuity design (RDD) in education research exploits a score-based eligibility cutoff — such as a test score threshold, GPA requirement, or age cutoff — to estimate the causal effect of a program, intervention, or policy on student or school outcomes. Units just below and just above the cutoff are treated as near-randomly assigned, enabling credible causal inference without a randomized trial.	Interrupted 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.