เปรียบเทียบวิธี
ดูวิธีที่เลือกเทียบกันแบบเคียงข้าง แถวที่ต่างกันจะถูกเน้นไว้
| การวิเคราะห์ความแปรปรวนร่วม (Multivariate Analysis of Variance - MANOVA)× | การวิเคราะห์ความแปรปรวนร่วม (ANCOVA)× | การวิเคราะห์จำแนก (Discriminant Analysis)× | |
|---|---|---|---|
| สาขาวิชา | สถิติศาสตร์ | สถิติศาสตร์ | สถิติศาสตร์ |
| ตระกูล≠ | Hypothesis test | Hypothesis test | Latent structure |
| ปีกำเนิด≠ | 1932 | 1932 | 1936 |
| ผู้ริเริ่ม≠ | Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.) | Ronald A. Fisher | Ronald A. Fisher |
| ประเภท≠ | Parametric multivariate mean comparison | Parametric group comparison with covariate control | Supervised classification and dimension reduction |
| แหล่งต้นตำรับ≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ |
| ชื่อเรียกอื่น≠ | Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA) | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| ที่เกี่ยวข้อง≠ | 5 | 4 | 4 |
| สรุป≠ | MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932. | 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). | 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. |
| ScholarGateชุดข้อมูล ↗ |
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