So sánh phương pháp

	Thí nghiệm phòng thí nghiệm mù đôi	Thực nghiệm phòng thí nghiệm giai thừa
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	Mid-20th century (widespread adoption ~1950s onward)	1926 (Fisher's factorial principle); laboratory application systematized mid-20th century
Người khởi xướng	Rooted in 19th-century pharmacological and psychological research traditions; systematized in clinical and experimental science through the 20th century	Ronald A. Fisher
Loại	Controlled experimental design with blinding	Experimental research design
Công trình gốc	Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560	Kirk, R. E. (2013). Experimental Design: Procedures for the Behavioral Sciences (4th ed.). Sage Publications. ISBN: 978-1412974455
Tên gọi khác	double-blind lab experiment, double-masked laboratory experiment, DB lab experiment, double-blind controlled lab study	factorial lab experiment, laboratory factorial design, factorial controlled experiment, multi-factor lab study
Liên quan	5	2
Tóm tắt	A double-blind laboratory experiment is a controlled experimental design conducted in a laboratory setting in which neither the participants nor the researchers directly administering the treatment know which condition each participant has been assigned to. This dual blinding, combined with the high degree of environmental control characteristic of laboratory settings, minimizes both participant expectancy effects and experimenter bias, making it one of the most rigorous designs available for isolating causal relationships between independent and dependent variables.	A factorial laboratory experiment is a controlled experimental design in which two or more independent variables (factors) are simultaneously manipulated, each at two or more levels, within a laboratory setting. This design allows researchers to estimate both the individual main effect of each factor and the interaction effects between factors — making it one of the most efficient and informative designs in behavioral, psychological, and natural science research.