Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Адаптивная экспериментальная конструкция с контрольной группой× | Экспериментальный дизайн с контрольной группой× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1994 (formal adaptive framework); wider adoption 2000s–2010s | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Автор метода≠ | Peter Bauer and Klaus Kohne (adaptive interim analysis framework, 1994); broader adaptive design methodology developed by Scott Chow and Mark Chang | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Тип≠ | Adaptive experimental design | Experimental research design |
| Основополагающий источник≠ | Chow, S.-C., & Chang, M. (2008). Adaptive Design Methods in Clinical Trials. Chapman and Hall/CRC. ISBN: 978-1584886760 | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Другие названия | adaptive controlled experiment, adaptive two-arm controlled design, adaptive parallel-group design, flexible controlled trial design | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Связанные | 4 | 4 |
| Сводка≠ | An adaptive control group experimental design is an experiment that assigns participants to at least one treatment arm and one concurrent control group, while allowing pre-specified modifications to the trial — such as sample size re-estimation, early stopping, or allocation ratio changes — based on accumulating data. Adaptations are governed by decision rules established before the study begins, preserving Type I error control while improving efficiency. | Control group experimental design is a fundamental experimental structure in which participants are assigned to at least two groups — a treatment group that receives the intervention and a control group that does not — so that the effect of the intervention can be isolated by comparing outcomes across groups. Randomisation of assignment strengthens causal inference by balancing known and unknown confounders. |
| ScholarGateНабор данных ↗ |
|
|