Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Desenho Experimental de Grupo Controle Cruzado× | Desenho Experimental Pré-teste-Pós-teste× | |
|---|---|---|
| Área | Delineamento experimental | Delineamento experimental |
| Família | Process / pipeline | Process / pipeline |
| Ano de origem≠ | Mid-20th century; systematic treatment from 1980s onward | 1963 (formalized in Campbell & Stanley) |
| Autor original≠ | Established in clinical pharmacology and agricultural research; formalized by B. Jones & M. G. Kenward | Donald T. Campbell and Julian C. Stanley |
| Tipo≠ | Experimental design | Experimental / quasi-experimental research design |
| Fonte seminal≠ | Jones, B., & Kenward, M. G. (2003). Design and Analysis of Cross-Over Trials (2nd ed.). Chapman and Hall/CRC. ISBN: 978-1584883500 | Campbell, D. T., & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research. Rand McNally. link ↗ |
| Outros nomes | crossover controlled trial, within-subject crossover with control, AB/BA crossover controlled design, repeated-measures crossover with control arm | pretest-posttest design, before-after design, pre-post design, two-wave experimental design |
| Relacionados≠ | 6 | 5 |
| Resumo≠ | A crossover control group experimental design is an experimental approach in which participants are randomly assigned to sequences of conditions that include both a treatment and a control (no-treatment or placebo) period, with each participant experiencing both the experimental and control conditions in succession. By using each participant as their own control across periods, this design sharply reduces between-subject variability and typically requires fewer participants than parallel group trials to achieve equivalent statistical power. | The pretest-posttest experimental design measures participants on the outcome variable before and after treatment, typically with random assignment to treatment and control groups. The difference between pre- and post-scores isolates the treatment effect from baseline variation, making this one of the most widely used frameworks in experimental and quasi-experimental research across education, psychology, medicine, and the social sciences. |
| ScholarGateConjunto de dados ↗ |
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