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| Reka Bentuk Eksperimen Kumpulan Kawalan Buta Berganda× | Reka Bentuk Eksperimen Kumpulan Kawalan× | |
|---|---|---|
| Bidang | Reka Bentuk Eksperimen | Reka Bentuk Eksperimen |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1930s–1950s (formalized in clinical trial methodology) | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| Pengasas≠ | 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 |
| Jenis | Experimental research design | Experimental research design |
| Sumber perintis≠ | 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 ↗ |
| Alias | 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 |
| Berkaitan≠ | 5 | 4 |
| Ringkasan≠ | 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. |
| ScholarGateSet data ↗ |
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