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| Thí nghiệm tự nhiên theo cấu trúc thừa số× | Phép thử kiểm soát ngẫu nhiên theo thừa số× | |
|---|---|---|
| Lĩnh vực | Thiết kế thí nghiệm | Thiết kế thí nghiệm |
| Họ | Process / pipeline | Process / pipeline |
| Năm ra đời≠ | 1920s (factorial origins, Fisher); natural experiment formalization 1990s–2000s; factorial natural experiment usage widespread 2000s–present | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| Người khởi xướng≠ | Extension of natural experiment tradition (Dunning, Angrist & Pischke) combined with factorial design logic (Fisher) | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| Loại≠ | Quasi-experimental research design | Experimental trial design |
| Công trình gốc≠ | Dunning, T. (2012). Natural Experiments in the Social Sciences: A Design-Based Approach. Cambridge University Press. ISBN: 978-1107698000 | Collins, L. M., Dziak, J. J., Kugler, K. C., & Trail, J. B. (2014). Factorial experiments: Efficient tools for evaluation of intervention components. American Journal of Preventive Medicine, 47(4), 498–504. DOI ↗ |
| Tên gọi khác≠ | factorial quasi-experiment, multi-factor natural experiment, factorial exogenous variation design | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| Liên quan≠ | 4 | 6 |
| Tóm tắt≠ | A factorial natural experiment exploits naturally occurring exogenous variation across two or more factors simultaneously, allowing researchers to estimate main effects and interactions without random assignment. Natural events, policy changes, or institutional rules create treatment conditions that approximate a factorial structure, enabling causal inference in observational settings where controlled experimentation is infeasible or unethical. | A factorial randomized controlled trial (factorial RCT) is an experimental design in which participants are randomly assigned to every possible combination of two or more independent factors (treatments or intervention components) simultaneously. This allows researchers to estimate the main effect of each factor and their interactions within a single, efficient trial, rather than running separate experiments for each factor. |
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