Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kovariācijas analīze (ANCOVA)× | Daudzvarianto kovariācijas analīze (MANCOVA)× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1932 | 1970 |
| Autors≠ | Ronald A. Fisher | Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s |
| Tips≠ | Parametric group comparison with covariate control | Parametric multivariate mean comparison with covariate control |
| Pirmavots≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541 |
| Citi nosaukumi≠ | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi |
| Saistītās≠ | 4 | 5 |
| Kopsavilkums≠ | ANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013). | MANCOVA (Multivariate Analysis of Covariance) is a parametric hypothesis test that simultaneously compares two or more groups on multiple continuous dependent variables while statistically controlling for one or more covariates. It extends MANOVA by incorporating covariate adjustment, a tradition consolidated in multivariate statistical methodology by the 1970s and authoritatively documented by Tabachnick and Fidell (2019). |
| ScholarGateDatu kopa ↗ |
|
|