Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Факториальный односубъектный экспериментальный дизайн× | Перекрестный односубъектный экспериментальный дизайн× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1970s–1980s | 1970s–1980s (single-case crossover formalized in behavioral research context) |
| Автор метода≠ | Applied behavior analysis tradition; systematized in Barlow & Hersen (1984) and Kazdin (1982) | Developed within the single-case research tradition; crossover application formalized by Barlow and Hersen and expanded by Kazdin |
| Тип≠ | Experimental single-subject design with multiple independent variables | Experimental single-subject design |
| Основополагающий источник | Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press. ISBN: 978-0195341881 | Kazdin, A. E. (2011). Single-Case Research Designs: Methods for Clinical and Applied Settings (2nd ed.). Oxford University Press. ISBN: 978-0195341881 |
| Другие названия | factorial SCED, factorial single-case design, factorial N-of-1 design, factorial within-subject experimental design | crossover SSED, alternating-treatments crossover design, single-case crossover design, N-of-1 crossover design |
| Связанные≠ | 6 | 4 |
| Сводка≠ | A factorial single-subject experimental design applies the logic of factorial experiments — manipulating two or more independent variables simultaneously to study main effects and interactions — within a single-subject (N=1 or small N) repeated-measures framework. Instead of comparing groups, the same individual serves as their own control across systematically varied conditions, enabling fine-grained analysis of how multiple treatment components combine to influence behavior or clinical outcomes. | The crossover single-subject experimental design (crossover SSED) applies two or more treatment conditions sequentially to the same individual, with a washout or return-to-baseline period between conditions. Because each participant serves as their own control, between-subject variability is eliminated, enabling precise causal inference about treatment effects even with very small samples — often a single participant. This design is widely used in applied behavior analysis, special education, rehabilitation, and clinical psychology. |
| ScholarGateНабор данных ↗ |
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