Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Diseño de Solomon de cuatro grupos doblemente ciego× | Diseño Experimental con Grupo de Control× | |
|---|---|---|
| Campo | Diseño experimental | Diseño experimental |
| Familia | Process / pipeline | Process / pipeline |
| Año de origen≠ | 1949 (Solomon design); double-blind blinding integrated in 20th-century experimental practice | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Autor original≠ | Richard L. Solomon (base design); double-blind protocol is a general methodological standard | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Tipo≠ | True experimental design | Experimental research design |
| Fuente seminal≠ | 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 ↗ |
| Alias | 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 |
| Relacionados≠ | 5 | 4 |
| Resumen≠ | 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. |
| ScholarGateConjunto de datos ↗ |
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