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| Eksperyment laboratoryjny typu crossover× | Randomizowane badanie krzyżowe× | |
|---|---|---|
| Dziedzina | Planowanie eksperymentów | Planowanie eksperymentów |
| Rodzina | Process / pipeline | Process / pipeline |
| Rok powstania≠ | Mid-20th century; consolidated 1980s–2000s | 1960s (Grizzle 1965 for statistical foundations); widely used in clinical research since the 1970s |
| Twórca≠ | Established in pharmacological and behavioral research; Jones & Kenward formalized the framework | Early formalized by statisticians including Bradford Hill and colleagues in clinical trials; theoretical framework developed by Grizzle (1965) and later Senn (2002) |
| Typ≠ | Within-subjects experimental design | Experimental within-subject design |
| Źródło pierwotne≠ | Jones, B., & Kenward, M. G. (2014). Design and Analysis of Cross-Over Trials (3rd ed.). CRC Press. ISBN: 978-1439861424 | Senn, S. (2002). Cross-over Trials in Clinical Research (2nd ed.). Wiley. ISBN: 978-0471496533 |
| Inne nazwy | within-subjects crossover lab study, repeated-measures crossover experiment, crossover controlled lab experiment, within-person laboratory crossover trial | crossover RCT, crossover trial, within-subject RCT, AB/BA crossover design |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | A crossover laboratory experiment is a within-subjects experimental design conducted in a controlled lab environment in which each participant receives two or more treatments sequentially, serving as their own control. By eliminating between-person variability from the error term, it yields high statistical power with relatively small samples. Treatment order is randomized or counterbalanced across participants to guard against order and carryover effects. | 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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