Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Jauktais ANOVA× | Kovariācijas analīze (ANCOVA)× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1925 | 1932 |
| Autors≠ | R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation | Ronald A. Fisher |
| Tips≠ | Parametric factorial ANOVA | Parametric group comparison with covariate control |
| Pirmavots≠ | Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE. ISBN: 978-1526419521 | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 |
| Citi nosaukumi≠ | split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı) | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) |
| Saistītās≠ | 6 | 4 |
| Kopsavilkums≠ | Mixed ANOVA is a parametric factorial analysis of variance that simultaneously examines at least one between-subjects factor and at least one within-subjects (repeated-measures) factor. Rooted in R. A. Fisher's ANOVA framework formalised in 1925, it is the standard method for experimental and longitudinal designs in which different groups are each measured across multiple time points or conditions. | 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). |
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