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Desain Regresi Diskontinuitas dalam Riset Pendidikan×Analisis Deret Waktu Terinterupsi (ITS)×
BidangInferensi KausalInferensi Kausal
KeluargaRegression modelRegression model
Tahun asal1960 (origination); 1999-2010 (education economics canon)2002
PencetusThistlethwaite & Campbell (1960); popularized in education economics by Angrist & Lavy (1999), Lee & Lemieux (2010)Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
TipeQuasi-experimental causal inferenceQuasi-experimental segmented regression
Sumber perintisLee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗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. DOI ↗
AliasRDD in education, education RD design, sharp RDD education, score-cutoff designITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Terkait55
RingkasanRegression 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.
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ScholarGateBandingkan metode: Regression discontinuity design in education research · Interrupted Time Series. Diakses 2026-06-20 dari https://scholargate.app/id/compare