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| 自适应试验设计× | 生态学研究× | |
|---|---|---|
| 领域≠ | 临床研究 | 流行病学 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s-2000s | 19th century (Snow 1854); formalised mid-20th century |
| 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 |
| 类型≠ | Research Design | Observational epidemiological study |
| 开创性文献≠ | Pocock, S. J. (2005). Current issues in the design and interpretation of clinical trials. BMJ, 330(7500), 1118–1121. link ↗ | Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗ |
| 别名≠ | adaptive trial, adaptive design, response-adaptive randomization, RAR | aggregate study, correlational study, ecological correlation study, population-level study |
| 相关≠ | 1 | 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. |
| ScholarGate数据集 ↗ |
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