Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Прагматический план Соломона для четырех групп× | Экспериментальный дизайн с контрольной группой× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1949 (Solomon design); pragmatic variant in applied use from 1990s onward | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Автор метода≠ | Solomon four-group design: Richard L. Solomon (1949); pragmatic orientation formalized by Schwartz & Lellouch (1967) and Thorpe et al. (2009) | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Тип≠ | Experimental design (pragmatic variant) | Experimental research design |
| Основополагающий источник≠ | Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46(2), 137–150. DOI ↗ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Другие названия | pragmatic S4GD, real-world Solomon four-group design, pragmatic pretest-control design, pragmatic Solomon design | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Связанные≠ | 5 | 4 |
| Сводка≠ | The Pragmatic Solomon Four-Group Design combines the pretest-sensitization control logic of the classic Solomon (1949) four-group structure with the broad eligibility, flexible delivery, and real-world conditions characteristic of pragmatic trials. Four groups are formed: two receive the intervention (one pretested, one not) and two serve as controls (one pretested, one not), allowing simultaneous estimation of treatment effects and pretest sensitization effects under ecologically valid settings. | 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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