Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Факторен експериментален дизайн с предварителен и финален тест× | ANOVA с повтарящи се измервания× | |
|---|---|---|
| Област≠ | Планиране на експеримента | Статистика |
| Семейство≠ | Process / pipeline | Hypothesis test |
| Година на възникване≠ | 1963 (canonical formalization) | 1992 |
| Създател≠ | Codified by Donald T. Campbell and Julian C. Stanley | Girden (textbook treatment); Field (2013) |
| Тип≠ | True experimental design | Parametric within-subjects mean comparison |
| Основополагащ източник≠ | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 |
| Други названия | factorial pre-post design, factorial repeated-measures pretest-posttest design, multi-factor pretest-posttest design, FPPD | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA |
| Свързани≠ | 6 | 4 |
| Резюме≠ | A factorial pretest-posttest experimental design combines the simultaneous manipulation of two or more independent variables (factors) with measurement of the dependent variable both before and after treatment. This structure allows researchers to assess the main effect of each factor, all possible interaction effects between factors, and the magnitude of change from pretest to posttest — all within a single, fully randomised experiment. | Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013). |
| ScholarGateНабор от данни ↗ |
|
|