Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Факторный дизайн ABAB× | Факторный эксперимент× | |
|---|---|---|
| Область | Планирование эксперимента | Планирование эксперимента |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1960s–1970s (integration of factorial and single-subject reversal traditions) | 1926–1935 |
| Автор метода≠ | Derived from Sidman (1960) reversal logic and Fisher & Yates factorial principles; systematized in applied behavior analysis | Ronald A. Fisher |
| Тип≠ | Single-subject experimental design | Quantitative experimental 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 | Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd. link ↗ |
| Другие названия | factorial reversal design, factorial withdrawal design, multi-factor ABAB design, factorial single-subject reversal | factorial design, factorial ANOVA design, multi-factor experiment, crossed-factor design |
| Связанные≠ | 5 | 6 |
| Сводка≠ | The factorial ABAB design embeds a factorial structure within the classical ABAB reversal framework, enabling a single participant or a small set of participants to experience multiple factor combinations across alternating baseline (A) and treatment (B) phases. By systematically withdrawing and reinstating treatment conditions that vary across two or more factors, the design allows examination of both main effects and interactions at the individual level, providing strong experimental control through within-subject replication. | A factorial experiment is an experimental design in which two or more independent variables (factors) are manipulated simultaneously, and every combination of their levels is tested. Introduced by Ronald Fisher in the 1920s–1930s, it is the standard approach whenever a researcher needs to detect not only the main effect of each factor but also whether the effect of one factor depends on the level of another — the interaction effect. |
| ScholarGateНабор данных ↗ |
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