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| Crossover-fraktionielles faktorielles Experiment× | Crossover-Randomisierter Kontrollierter Versuch× | |
|---|---|---|
| Fachgebiet | Versuchsplanung | Versuchsplanung |
| Familie | Process / pipeline | Process / pipeline |
| Entstehungsjahr≠ | 1950s–1970s (fractional factorial from 1940s; crossover integration from 1960s–1970s) | 1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s |
| Urheber≠ | Box, Hunter & Hunter (fractional factorial); Senn & Williams (crossover integration) | Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002) |
| Typ≠ | Within-subject multi-factor experimental design | Experimental within-subject design |
| Wegweisende Quelle | Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533 | Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533 |
| Aliasnamen | crossover FF design, within-subject fractional factorial, repeated-measures fractional factorial, crossover FFE | crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design |
| Verwandt | 5 | 5 |
| Zusammenfassung≠ | A crossover fractional factorial experiment is a within-subject design in which each participant receives a strategically chosen subset of all possible factor-level combinations in a defined sequence, with washout periods between treatment periods. By combining the run-economy of fractional factorial designs with the within-subject efficiency of crossover designs, it allows estimation of main effects and selected interactions while controlling for between-subject variability using far fewer participants and experimental runs than a full factorial crossover. | 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. |
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