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| Експериментален дизайн с двойно заслепена контролна група× | Експериментален дизайн с контролна група× | |
|---|---|---|
| Област | Планиране на експеримента | Планиране на експеримента |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1930s–1950s (formalized in clinical trial methodology) | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Създател≠ | R. A. Fisher (experimental control foundations); blinding practices evolved in clinical research through the 20th century | Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley |
| Тип | Experimental research design | Experimental research design |
| Основополагащ източник≠ | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Други названия | double-blind controlled experiment, DB-CG design, double-masked controlled trial, double-blind controlled study | controlled experiment, true experimental design, randomized controlled design, treatment-control design |
| Свързани≠ | 5 | 4 |
| Резюме≠ | A double-blind control group experimental design is a rigorous experimental structure in which participants are randomly assigned to at least one treatment group and one control group, while both the participants and the researchers collecting or assessing outcomes are kept unaware of group assignment. By combining allocation concealment with blinding at two levels, the design minimizes expectancy bias, placebo effects, and assessor bias simultaneously, making it a cornerstone of high-quality intervention research in medicine, psychology, and the social sciences. | 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 от данни ↗ |
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