Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Experiment factorial pragmatic complet× | Experiment factorial randomizat pe clustere× | |
|---|---|---|
| Domeniu | Design experimental | Design experimental |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1920s (factorial); 1967/2009 (pragmatic framework) | 1990s (formalized in group-randomized trial literature) |
| Autorul original≠ | Full factorial: R.A. Fisher (1920s); Pragmatic framing: Schwartz & Lellouch (1967), formalized by Thorpe et al. (2009) | David M. Murray and colleagues; Allan Donner & Neil Klar |
| Tip | Experimental design | Experimental design |
| Sursa seminală≠ | Thorpe, K. E., Zwarenstein, M., Oxman, A. D., Treweek, S., Furberg, C. D., Altman, D. G., ... & Chalmers, I. (2009). A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. Journal of Clinical Epidemiology, 62(5), 464-475. DOI ↗ | Murray, D. M. (1998). Design and Analysis of Group-Randomized Trials. Oxford University Press. ISBN: 978-0195120912 |
| Denumiri alternative | pragmatic factorial trial, real-world full factorial design, effectiveness full factorial experiment, pragmatic 2^k experiment | cluster-randomized factorial design, group-randomized factorial trial, CRT factorial, clustered factorial experiment |
| Înrudite≠ | 6 | 5 |
| Rezumat≠ | A pragmatic full factorial experiment combines the complete crossing of all factor levels (the full factorial structure) with the broad eligibility criteria, flexible delivery, and real-world conditions of a pragmatic trial. Every possible combination of factors is tested simultaneously, yielding both main effects and all interaction effects, while deliberately relaxing strict laboratory controls to reflect how interventions actually operate in practice. | A cluster randomized factorial experiment assigns intact groups (clusters such as schools, clinics, or communities) at random to all combinations of two or more treatment factors, enabling simultaneous evaluation of multiple interventions and their interactions while respecting the natural grouping of participants. It merges the logistical and ethical advantages of cluster randomization with the efficiency of factorial design. |
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