Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Прагматическая экспериментальная конструкция с контрольной группой× | Экспериментальный дизайн с контрольной группой× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1967 (seminal distinction); 2009 (PRECIS operationalization) | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Автор метода≠ | Schwartz & Lellouch (pragmatic vs explanatory distinction); extended by PRECIS framework (Thorpe et al.) | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Тип≠ | Experimental design (pragmatic variant) | Experimental research design |
| Основополагающий источник≠ | Schwartz, D., & Lellouch, J. (1967). Explanatory and pragmatic attitudes in therapeutical trials. Journal of Chronic Diseases, 20(8), 637–648. DOI ↗ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Другие названия | pragmatic controlled trial, effectiveness trial with control group, real-world control group design, pragmatic comparative design | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Связанные≠ | 6 | 4 |
| Сводка≠ | 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. | Control group experimental design is a fundamental experimental structure in which participants are assigned to at least two groups — a treatment group that receives the intervention and a control group that does not — so that the effect of the intervention can be isolated by comparing outcomes across groups. Randomisation of assignment strengthens causal inference by balancing known and unknown confounders. |
| ScholarGateНабор данных ↗ |
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