পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| প্রাগম্যাটিক র্যান্ডমাইজড কন্ট্রোলড ট্রায়াল× | ফ্যাক্টোরিয়াল র্যান্ডমাইজড কন্ট্রোলড ট্রায়াল× | |
|---|---|---|
| ক্ষেত্র | পরীক্ষামূলক নকশা | পরীক্ষামূলক নকশা |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 1967 | 1926 (Fisher factorial foundations); 2000s–2010s (clinical factorial RCT formalization) |
| প্রবর্তক≠ | Daniel Schwartz and Joseph Lellouch | R. A. Fisher (factorial design foundations); adapted into clinical trials via MOST framework (Collins et al., 2014) |
| ধরন≠ | Experimental design — pragmatic trial | Experimental trial design |
| মৌলিক উৎস≠ | Schwartz, D., & Lellouch, J. (1967). Explanatory and pragmatic attitudes in therapeutical trials. Journal of Chronic Diseases, 20(8), 637–648. DOI ↗ | 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 ↗ |
| অপর নাম | pRCT, pragmatic trial, practical clinical trial, real-world RCT | Factorial RCT, factorial trial, multi-factor RCT, factorial experiment with randomization |
| সম্পর্কিত≠ | 4 | 6 |
| সারসংক্ষেপ≠ | A pragmatic randomized controlled trial (pRCT) tests whether an intervention works under ordinary, real-world conditions — broad eligibility, flexible delivery, and routine care settings. Participants are still randomly assigned to treatment or control, preserving causal inference, but the study is designed to reflect the diversity and variability of actual practice rather than the ideal conditions of an explanatory trial. The defining framework is the PRECIS-2 tool, which maps any RCT along nine pragmatic-to-explanatory dimensions. | 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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