เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การออกแบบการทดลองแบบกลุ่มควบคุมอำพรางสองฝ่าย× | การออกแบบการทดลองแบบมีกลุ่มควบคุม× | |
|---|---|---|
| สาขาวิชา | การออกแบบการทดลอง | การออกแบบการทดลอง |
| ตระกูล | Process / pipeline | Process / pipeline |
| ปีกำเนิด≠ | 1930s–1950s (formalized in clinical trial methodology) | 1935 (Fisher); 1963 (Campbell & Stanley codification) |
| ผู้ริเริ่ม≠ | 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 |
| ประเภท | Experimental research design | Experimental research design |
| แหล่งต้นตำรับ≠ | 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 ↗ |
| ชื่อเรียกอื่น | 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 |
| ที่เกี่ยวข้อง≠ | 5 | 4 |
| สรุป≠ | 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. |
| ScholarGateชุดข้อมูล ↗ |
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