Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Многомерное каузально-сравнительное исследование× | Дискриминантный анализ× | |
|---|---|---|
| Область≠ | Дизайн исследования | Статистика |
| Семейство≠ | Process / pipeline | Latent structure |
| Год появления≠ | Mid-20th century onward; multivariate extension systematized 1970s–1990s | 1936 |
| Автор метода≠ | Extension of causal-comparative tradition (cf. Chapin, 1947; Gay, Mills & Airasian) | Ronald A. Fisher |
| Тип≠ | Quantitative non-experimental comparative design | Supervised classification and dimension reduction |
| Основополагающий источник≠ | Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to Design and Evaluate Research in Education (10th ed.). McGraw-Hill. ISBN: 978-1260085594 | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ |
| Другие названия | multivariate causal-comparative design, MANOVA causal-comparative study, multi-outcome ex post facto research, multivariate ex post facto design | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| Связанные≠ | 6 | 4 |
| Сводка≠ | Multivariate causal-comparative research is a quantitative, non-experimental design that investigates whether pre-existing group differences (defined by a naturally occurring categorical variable) are associated with differences across multiple outcome variables considered simultaneously. By extending the classic causal-comparative framework to several dependent variables at once, it reduces Type I error inflation and captures the correlated structure of outcomes that univariate comparisons would miss. | Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error. |
| ScholarGateНабор данных ↗ |
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