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Çok değişkenli varyans analizinde kovaryans matrislerinin homojenliği ön şartı

The assumption of equality of population covariance matrices in manova

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  1. Tez No: 83390
  2. Yazar: EMİNE ARZU KANIK
  3. Danışmanlar: PROF.DR. FİKRET GÜRBÜZ
  4. Tez Türü: Doktora
  5. Konular: Ziraat, Agriculture
  6. Anahtar Kelimeler: Multivariate analysis of variance, equality of covariance matrices, assumptions, simulation study, Benzetim, Kovaryans matrisleri, Zootekni, Çok değişkenli varyans analizi, Multivariate analysis of variance, equality of covariance matrices, assumptions, simulation study, Simulation, Covariance matrices, Zootechnics, Multivariate variance analysis
  7. Yıl: 1999
  8. Dil: Türkçe
  9. Üniversite: Ankara Üniversitesi
  10. Enstitü: Fen Bilimleri Enstitüsü
  11. Ana Bilim Dalı: Zootekni Ana Bilim Dalı
  12. Bilim Dalı: Belirtilmemiş.
  13. Sayfa Sayısı: Belirtilmemiş.

Özet

ABSTRACT Ph.D. Thesis THE ASSUMPTION OF EQUALITY OF POPULATION COVARUNCE MATRICES I N MANOVA Emine Arzu KANIK Ankara University Graduate School of Natural and Applied Sciences Department of Animal Sciences Supervisor: Prof.Dr. Fikret GÜRBÜZ In this study, equality of covariance matrices assumptions in MANOVA were investigated with simulation study. In simulation study, all samples generated from multivariate normal distribution and all observations in each group are independent In this study total number of combinations is 8175 and each combination simulated 10000 times. Most of researchers shown that inequality of covariance matrices effect type I error and Hotelling's T2, Wilks Lambda, Roys Largest Root and Pillai's V tests criteria» in MANOVA are not robust when this assumption are not met As a result not equal sample size and number of dependent variable bad effect on type I error when this assumption are not met Whenever number of dependent variables is 2 or 3 all test statistics except Roy' s (R) are generally robust For 10 dependent variables actual a is too big or small it depends on which group has large sample size. In this study calculated two new constans DP and K. There is a high relation between actual a and K. 1999,116 pages

Özet (Çeviri)

ABSTRACT Ph.D. Thesis THE ASSUMPTION OF EQUALITY OF POPULATION COVARUNCE MATRICES I N MANOVA Emine Arzu KANIK Ankara University Graduate School of Natural and Applied Sciences Department of Animal Sciences Supervisor: Prof.Dr. Fikret GÜRBÜZ In this study, equality of covariance matrices assumptions in MANOVA were investigated with simulation study. In simulation study, all samples generated from multivariate normal distribution and all observations in each group are independent In this study total number of combinations is 8175 and each combination simulated 10000 times. Most of researchers shown that inequality of covariance matrices effect type I error and Hotelling's T2, Wilks Lambda, Roys Largest Root and Pillai's V tests criteria» in MANOVA are not robust when this assumption are not met As a result not equal sample size and number of dependent variable bad effect on type I error when this assumption are not met Whenever number of dependent variables is 2 or 3 all test statistics except Roy' s (R) are generally robust For 10 dependent variables actual a is too big or small it depends on which group has large sample size. In this study calculated two new constans DP and K. There is a high relation between actual a and K. 1999,116 pages

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