Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Дизайн Соломона с четырьмя группами и двойным ослеплением× | Экспериментальный дизайн с контрольной группой× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1949 (Solomon design); double-blind blinding integrated in 20th-century experimental practice | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Автор метода≠ | Richard L. Solomon (base design); double-blind protocol is a general methodological standard | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Тип≠ | True experimental design | 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 | double-blind S4GD, blinded Solomon design, double-blind four-group design, Solomon four-group with double-blind | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Связанные≠ | 5 | 4 |
| Сводка≠ | The double-blind Solomon four-group design combines Richard Solomon's classic four-group structure — which isolates pretest sensitization effects — with double-blind blinding, ensuring that neither participants nor outcome assessors know group assignments. This combination yields high internal validity by controlling simultaneously for testing effects, expectancy bias, and experimenter influence, making it one of the most rigorous true experimental designs available. | 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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