So sánh phương pháp

	Thí nghiệm thực địa chéo (Crossover Field Experiment)	Thử nghiệm đối chứng ngẫu nhiên bắt chéo
Lĩnh vực	Thiết kế thí nghiệm	Thiết kế thí nghiệm
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1960s–1970s (field experiment framework); crossover application in non-clinical fields from 1980s onward	1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s
Người khởi xướng	Crossover design principles attributed to R. A. Fisher (1930s); field experiment tradition developed by Donald T. Campbell and Julian Stanley (1960s)	Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002)
Loại	Within-subject experimental design conducted in naturalistic settings	Experimental within-subject design
Công trình gốc	Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). John Wiley & Sons. ISBN: 978-0471496533	Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533
Tên gọi khác	within-subject field experiment, crossover field trial, repeated-measures field experiment, field crossover design	crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design
Liên quan	5	5
Tóm tắt	A crossover field experiment is a within-subject experimental design conducted outside the laboratory in naturalistic, real-world settings. Each participant or unit receives multiple treatments in a randomized sequence, separated by washout periods, allowing researchers to observe causal effects while each unit serves as its own control. This approach combines the internal validity of crossover designs with the ecological validity characteristic of field experimentation.	A crossover randomized controlled trial (crossover RCT) is an experimental design in which each participant receives all study interventions in a randomized sequence, separated by a washout period. Because every participant serves as their own control, within-subject variability is eliminated from the treatment comparison, yielding greater statistical power per participant than a parallel-group RCT of equal size.