Salīdzināt metodes

	Salomona četru grupu krusteniskais plāns	Krustojuma randomizēts kontrolētais pētījums
Nozare	Eksperimentu plānošana	Eksperimentu plānošana
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1949 (base design); crossover adaptation developed through later methodological literature	1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s
Autors	Richard L. Solomon (base design); crossover extension via repeated-measures methodology	Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002)
Tips	Experimental design (pretest-sensitization control + within-subjects crossover)	Experimental within-subject design
Pirmavots	Solomon, R. L. (1949). An extension of control group design. Psychological Bulletin, 46(2), 137–150.	Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533
Citi nosaukumi	crossover S4G design, within-subjects Solomon design, repeated-measures Solomon four-group design	crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design
Saistītās	5	5
Kopsavilkums	The Crossover Solomon Four-Group Design merges two powerful experimental strategies: the Solomon four-group design's control for pretest sensitization and the crossover design's within-subjects efficiency. Participants are randomly assigned to one of four groups that vary in whether they receive a pretest and in the sequence of treatment and control conditions, allowing the researcher to simultaneously estimate treatment effects, pretest effects, and their interaction while controlling for individual differences through repeated measurement.	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.