방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 다중 팔 실험× | 요인 실험× | |
|---|---|---|
| 분야 | 실험설계 | 실험설계 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1990s–2000s (clinical formalization); multi-arm concept implicit in ANOVA-era factorial designs | 1926–1935 |
| 창시자≠ | Developed within clinical trials methodology; formalized by Parmar, Royston and colleagues (UK MRC CTU, early 2000s) | Ronald A. Fisher |
| 유형≠ | Experimental design | Quantitative experimental design |
| 원전≠ | Royston, P., Parmar, M. K. B., & Qian, W. (2003). Novel designs for multi-arm clinical trials with survival outcomes with an application in ovarian cancer. Statistics in Medicine, 22(14), 2239–2256. DOI ↗ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| 별칭 | multi-arm trial, multiple-arm experiment, multi-group experiment, many-arm design | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design |
| 관련≠ | 5 | 6 |
| 요약≠ | A multi-arm experiment simultaneously compares three or more treatment or intervention conditions — each called an arm — against a shared control or against one another. By testing multiple alternatives in a single study, it yields more information per participant than running separate two-group experiments sequentially, while controlling the overall Type I error rate through pre-specified comparison strategies. | A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect. |
| ScholarGate데이터셋 ↗ |
|
|