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Kaedah Kawalan Sintetik (SCM)×Analisis Siri Masa Terganggu (ITS)×
BidangInferens KausalInferens Kausal
KeluargaRegression modelRegression model
Tahun asal20102002
PengasasAbadie, Diamond & HainmuellerWagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
JenisCounterfactual causal-inference modelQuasi-experimental segmented regression
Sumber perintisAbadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505. 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 ↗
Aliassynthetic control method, SCM, synthetic counterfactual, Sentetik Kontrol Yöntemi (SCM)ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
Berkaitan55
RingkasanThe Synthetic Control Method, introduced by Abadie, Diamond and Hainmueller in 2010, builds a weighted counterfactual for a single treated unit from a pool of untreated donor units. It is widely regarded as the gold standard for evaluating large policy interventions, natural experiments, and N=1 case studies where no obvious comparison unit exists.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 kaedah: Synthetic Control · Interrupted Time Series. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare