Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Дизайн Соломона с четырьмя группами и двойным ослеплением× | Факторный эксперимент× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1949 (Solomon design); double-blind blinding integrated in 20th-century experimental practice | 1926–1935 |
| Автор метода≠ | Richard L. Solomon (base design); double-blind protocol is a general methodological standard | Ronald A. Fisher |
| Тип≠ | True experimental design | Quantitative experimental design |
| Основополагающий источник≠ | Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46(2), 137–150. DOI ↗ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Другие названия | double-blind S4GD, blinded Solomon design, double-blind four-group design, Solomon four-group with double-blind | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design |
| Связанные≠ | 5 | 6 |
| 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. | A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect. |
| ScholarGateНабор данных ↗ |
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