So sánh phương pháp

	Thí nghiệm tự nhiên thích ứng	Thí nghiệm tự nhiên
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	2000s–2010s (systematic application in policy and social science evaluation)	1990s (formal methodological articulation); earlier in epidemiology (John Snow, 1854)
Người khởi xướng	Synthesizes natural experiment tradition (Meyer 1995; Dunning 2012) with adaptive design principles (Wald 1947; Chow & Chang 2008)	Varied; systematized in econometrics and political science (e.g., Meyer 1995; Angrist & Krueger 1991)
Loại	Quasi-experimental adaptive research design	Quasi-experimental research design
Công trình gốc	Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press. ISBN: 978-1107698000	Meyer, B. D. (1995). Natural and quasi-experiments in economics. Journal of Business and Economic Statistics, 13(2), 151–161.
Tên gọi khác	adaptive quasi-experiment, adaptive exogenous shock design, adaptive as-if randomization, sequential natural experiment	natural quasi-experiment, naturally occurring experiment, exogenous shock design, as-if randomization
Liên quan	4	3
Tóm tắt	An adaptive natural experiment combines the causal logic of the natural experiment — exploiting real-world events that assign individuals to conditions in a plausibly exogenous way — with pre-specified adaptive monitoring rules that allow the analytic protocol to be modified based on accumulating data. This hybrid design is used in economics, epidemiology, and policy evaluation when the natural event unfolds over time and interim evidence can legitimately inform decisions about data collection scope, subgroup focus, or analytic strategy without compromising causal validity.	A natural experiment exploits a real-world event, policy, or circumstance that assigns individuals to treatment and control conditions in a way that is plausibly random — or at least exogenous to the outcome of interest. Because the researcher does not control assignment, it occupies a middle ground between a true randomized controlled trial and purely observational research, offering stronger causal leverage than conventional observational designs when the as-if randomization assumption holds.