方法对比

	自适应试验设计	生态学研究	中断时间序列（ITS）分析
领域	临床研究	流行病学	因果推断
方法族	Process / pipeline	Process / pipeline	Regression model
起源年份	1990s-2000s	19th century (Snow 1854); formalised mid-20th century	2002
提出者	Stephen Pocock, Christopher Jennison, and statistical methodologists; FDA formalized guidance 2019	Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues	Wagner, Soumerai, Zhang & Ross-Degnan (segmented regression); Bernal, Cummins & Gasparrini (tutorial)
类型	Research Design	Observational epidemiological study	Quasi-experimental segmented regression
开创性文献	Pocock, S. J. (2005). Current issues in the design and interpretation of clinical trials. BMJ, 330(7500), 1118–1121.	Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81.	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.
别名	adaptive trial, adaptive design, response-adaptive randomization, RAR	aggregate study, correlational study, ecological correlation study, population-level study	ITS analysis, segmented regression of time series, Kesintili Zaman Serisi (ITS) Analizi
相关	1	5	5
摘要	An adaptive trial design allows pre-specified modifications to the trial based on interim data—such as sample size re-estimation, stopping for futility or efficacy, dropping ineffective arms, or shifting randomization ratios toward better-performing treatments. Developed systematically in the 1990s–2000s by statisticians like Pocock and Jennison, and formalized by the FDA in 2019, adaptive designs accelerate drug development, reduce exposure to ineffective treatments, and improve efficiency without inflating false-positive rates when properly executed.	An ecological study is an observational epidemiological design in which the unit of analysis is a group or population — a country, region, city, or time period — rather than an individual. Exposures and outcomes are measured as aggregates (rates, proportions, or means) and then correlated across groups to generate or evaluate hypotheses about population-level associations between risk factors and disease.	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.