A Monte Carlo Simulation Study Robustness of MANOVA Test Statistics in Bernoulli Distribution
Öz
The aim
of this study is to compare the robustness of Manova test statistics against
Type I error rate using the Monte Carlo simulation technique. In the method,
numbers are generated according to constant and increasing variance for g=3,4,5 group p=3,5,7 dependent variables n=10,30,60
sample size using the R. Numbers have been produced using these 54
combinations. Pillai Trace test statistic has been the least deviating from the
nominal α =0.05
value. Wilk Lambda and Hotelling-Lawley Trace test results were close to each
other. The researchers can decide according to the comparison results of the
analysis's suggested decision stage.
Anahtar Kelimeler
Kaynakça
- [1] Wilks, S.S., 1932. Certain generalizations made in the analysis of variance, Biometrica 24:471-494.
- [2] Johnson, R. A.. Wichern D. W., 1982. Applied Multivariate Statistical Analysis. Prentice-Hall, Inc. USA,594s.
- [3] Bartlett, M.S., 1954. A Note on the Multiplying Factors for Various chi-square pproximations. Journal of the Royal Statistical Society Series B (Methodological):pp 296-298.
- [4] Seber, G. A. F., 1984. Multivariate Observations. John Wiley & sons, Inc., USA,686.
- [5] Lawley, D. N., 1939. A generalization of Fisher's z test. Biometrika 30: 467-469.
- [6] Hotelling, H., 1931. The generalization of student's ratio. Annals of Mathematical Statistics 2: 360-378.
- [7] Pillai, K.C.S., 1955. Some New Test Criteria in Multivariate Analysis. The Annals of Mathematical Statistics 26:117-121.
- [8] Davis, A.W.,1980. On The Effects Of Nonnormality On The Likelihood Ratio Criterion Wilks's Moderate Multyvariate. The Journal Of the American Statistical Association 67:419-427.
Ayrıntılar
Birincil Dil
İngilizce
Konular
-
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
20 Eylül 2018
Gönderilme Tarihi
26 Nisan 2018
Kabul Tarihi
28 Eylül 2018
Yayımlandığı Sayı
Yıl 2018 Cilt: 22 Sayı: 3
Cited By
Applying Permanova for Multivariate Analysis of Variance in Health Studies
Black Sea Journal of Engineering and Science
https://doi.org/10.34248/bsengineering.1611775