Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Design experimental cu grup de control pragmatic× | Design experimental factorial cu grup de control× | |
|---|---|---|
| Domeniu | Design experimental | Design experimental |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1967 (seminal distinction); 2009 (PRECIS operationalization) | 1926–1935 |
| Autorul original≠ | Schwartz & Lellouch (pragmatic vs explanatory distinction); extended by PRECIS framework (Thorpe et al.) | Ronald A. Fisher |
| Tip≠ | Experimental design (pragmatic variant) | Experimental design |
| Sursa seminală≠ | Schwartz, D., & Lellouch, J. (1967). Explanatory and pragmatic attitudes in therapeutical trials. Journal of Chronic Diseases, 20(8), 637–648. DOI ↗ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Denumiri alternative | pragmatic controlled trial, effectiveness trial with control group, real-world control group design, pragmatic comparative design | factorial controlled experiment, factorial design with control, factorial RCT with control arm, multi-factor controlled experiment |
| Înrudite | 6 | 6 |
| Rezumat≠ | A pragmatic control group experimental design tests whether an intervention works under routine, real-world conditions by comparing it against a control condition — typically usual care or an active comparator — rather than a tightly controlled placebo. It prioritises external validity and applicability over the internal purity of an explanatory efficacy trial, asking whether an intervention makes a meaningful difference to people as they are actually treated in practice. | A factorial control group experimental design crosses two or more independent variables (factors) in a fully factorial structure while including at least one condition that serves as a no-treatment or standard-treatment control. This allows researchers to simultaneously estimate the main effect of each factor, their interactions, and the size of those effects relative to a meaningful baseline, maximising both causal precision and experimental efficiency. |
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