So sánh phương pháp

	Thiết kế nghiên cứu thực nghiệm nhóm chứng giả dược	Thiết kế Thí nghiệm Nhóm Đối chứng
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	Mid-20th century; widely formalized by 1980s–2000s	1935 (Fisher); 1963 (Campbell & Stanley codification)
Người khởi xướng	Established through clinical and behavioral research traditions; formalized by Bradford Hill and colleagues in mid-20th century trial methodology	Ronald A. Fisher; systematised by Donald T. Campbell & Julian C. Stanley
Loại	Experimental design (pilot/feasibility variant)	Experimental research design
Công trình gốc	Thabane, L., Ma, J., Chu, R., Cheng, J., Ismaila, A., Rios, L. P., Robson, R., Thabane, M., Giangregorio, L., & Goldsmith, C. H. (2010). A tutorial on pilot studies: the what, why and how. BMC Medical Research Methodology, 10, 1.	Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally.
Tên gọi khác	pilot controlled experiment, pilot RCT feasibility study, small-scale controlled trial, pilot control group study	controlled experiment, true experimental design, randomized controlled design, treatment-control design
Liên quan	4	4
Tóm tắt	A pilot control group experimental design is a small-scale, preliminary experiment that includes both a treatment group and a control group, conducted before the main study to test whether the full trial is feasible. It produces early effect-size estimates, identifies protocol problems, and confirms that random (or systematic) assignment to conditions is workable — all while generating a genuine comparison between treated and untreated participants.	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.