Salīdzināt metodes

	Pragmatiskais pilna faktoriālā eksperiments	Pragmatiskais faktoriālais eksperiments
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1920s (factorial); 1967/2009 (pragmatic framework)	2000s–2010s (formal integration)
Autors	Full factorial: R.A. Fisher (1920s); Pragmatic framing: Schwartz & Lellouch (1967), formalized by Thorpe et al. (2009)	Synthesized from pragmatic trial methodology (Schwartz & Lellouch, 1967) and factorial design principles (Fisher, 1935); formalized in clinical research contexts in the 2000s–2010s
Tips	Experimental design	Experimental trial design
Pirmavots	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.	Loudon, K., Treweek, S., Sullivan, F., Donnan, P., Thorpe, K. E., & Zwarenstein, M. (2015). The PRECIS-2 tool: designing trials that are fit for purpose. BMJ, 350, h2147.
Citi nosaukumi	pragmatic factorial trial, real-world full factorial design, effectiveness full factorial experiment, pragmatic 2^k experiment	pragmatic factorial trial, pragmatic factorial RCT, real-world factorial design, PFE
Saistītās	6	3
Kopsavilkums	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 pragmatic factorial experiment combines two powerful methodological frameworks: the factorial experimental design — which tests multiple intervention components simultaneously — and the pragmatic trial orientation, which prioritizes real-world applicability, broad eligibility criteria, and flexible delivery conditions. The result is a design that efficiently evaluates which components of a complex intervention work, and whether they interact, while maintaining ecological validity for health, behavioral, and educational research.