Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Split-Plot Design× | ANOVA de medidas repetidas× | |
|---|---|---|
| Área≠ | Delineamento experimental | Estatística |
| Família | Hypothesis test | Hypothesis test |
| Ano de origem≠ | 1935 | 1992 |
| Autor original≠ | Frank Yates | Girden (textbook treatment); Field (2013) |
| Tipo≠ | Parametric mixed-model ANOVA | Parametric within-subjects mean comparison |
| Fonte seminal≠ | Yates, F. (1935). Complex Experiments. Supplement to the Journal of the Royal Statistical Society, 2(2), 181–247. DOI ↗ | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 |
| Outros nomes≠ | split-plot ANOVA, whole-plot sub-plot design, Bölünmüş Parsel Deseni (Split-Plot) | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA |
| Relacionados≠ | 6 | 4 |
| Resumo≠ | The split-plot design is a parametric experimental design that applies one factor to large whole plots and a second factor to subdivisions (sub-plots) within each whole plot. It was introduced by Frank Yates in 1935 to handle agricultural experiments where one factor — such as irrigation or tillage method — is difficult or impractical to change frequently, while a second factor can be varied more easily within the same plot. | 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). |
| ScholarGateConjunto de dados ↗ |
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