TY  - JOUR
T1  - A Monte Carlo Simulation Study Robustness of MANOVA Test Statistics in Bernoulli Distribution
TT  - MANOVA Test İstatistiklerinin Monte-Carlo Simülasyonu ile Bernoulli Dağılımında Karşılaştırılması
AU  - Koç, Şeyma
AU  - Şahin, Mustafa
PY  - 2018
DA  - September
DO  - 10.19113/sdufenbed.469282
JF  - Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi
JO  - J. Nat. Appl. Sci.
PB  - Süleyman Demirel University
WT  - DergiPark
SN  - 1308-6529
SP  - 1125
EP  - 1131
VL  - 22
IS  - 3
LA  - en
AB  - The aimof this study is to compare the robustness of Manova test statistics againstType 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=10,30,60sample size using the R. Numbers have been produced using these 54combinations. Pillai Trace test statistic has been the least deviating from thenominal α =0.05value. Wilk Lambda and Hotelling-Lawley Trace test results were close to eachother. The researchers can decide according to the comparison results of theanalysis's suggested decision stage.
KW  - Manova test statistics
KW  - Simulation study
KW  - Monte Carlo
N2  - Buçalışmanın amacı, Manova test istatistiklerinin sağlamlığını Monte Carlosimülasyonunu kullanılarak I.tip hata bakımından kıyaslamaktır. Yöntemde,sayılar g = 3,4,5 grup için p = 3,5,7 bağımlı değişkene ait n = 10,30,60örneklem büyüklüğü kullanılarak sabit ve artan varyansta R programlama dilikullanılarak üretilmiştir. 54 kombinasyonda hesaplanan I.Tip hatalardan,nominal α =0.05 değerinden en azuzaklaşan test istatistiği Pillai İz test istatistiği olmuştur. Wilk Lambda veHotelling-Lawley İz test istatistikleri ise birbirlerine yakın sonuçvermişlerdir. Araştırıcılar analizlerinin karar aşamasında önerilen kıyaslamasonuçlarına göre karar verebilirler.
CR  - [1]	Wilks, S.S., 1932. Certain generalizations made in the analysis of variance, Biometrica 24:471-494.
CR  - [2]	Johnson, R. A.. Wichern D. W., 1982. Applied Multivariate Statistical Analysis. Prentice-Hall, Inc. USA,594s.
CR  - [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.
CR  - [4]	Seber, G. A. F., 1984. Multivariate Observations. John Wiley & sons, Inc., USA,686.
CR  - [5]	Lawley, D. N., 1939. A generalization of Fisher's z test. Biometrika 30: 467-469.
CR  - [6]	Hotelling, H., 1931. The generalization of student's ratio. Annals of Mathematical Statistics 2: 360-378.
CR  - [7]	Pillai, K.C.S., 1955. Some New Test Criteria in Multivariate Analysis. The Annals of Mathematical Statistics 26:117-121.
CR  - [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.
CR  - [9]	Davis, A. W., 1982. On The Effects Of The Moderate Multivariate Nonnormality On Roy's Largest Root Tests. The Journal Of the American Statistical Association 77:986-990.
CR  - [10]	Holloway, L.N., Dunn O.J., 1967. The robestness of Hotelling's T2. The Journal Of the American Statistical Association 62:124-136.
CR  - [11]	Olson, C.L., 1974. Copperative Robustness Of Multivariate Analysis Of Six Tests In Variance. The Journal Of the American Association 69 (348): 894-907.
CR  - [12]	Ito, K., 1969. On The Effect Of Homoscedasticity And Nonnormality Upon Some Multivariate Procedures. In Multivariate Analysis 2:87-120.
CR  - [13]	Korin, B.P.,1972. Some comment on the Homoscedasticity Criterion M and the multivariate analysis of varia as test T2 , W. and R. Biometrica 59:215-216.
CR  - [14]	Hopkins, J.W., Clay P.P.F., 1963. Some Bivariate Distribution Of Emprical T2 And Homoscedasticity Criterion M Under Unecual Variance And Leptokurtosis. The Journal Of the American Statistical Association 58:1048-1053.
UR  - https://doi.org/10.19113/sdufenbed.469282
L1  - https://dergipark.org.tr/en/download/article-file/551652
ER  -