Researchers can get help from these suggested results during their own study.
📌 3 Key Takeaways
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Objective & Hypothesis:The aim of this study is to compare the robustness of Manova test statistics against the Type I error rate using the Monte Carlo simulation in Bernoulli and Uniform distribution.
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Key Findings & Data:In the method, numbers have been 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 RStudio.
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Conclusion & Impact:Researchers can get help from these suggested results during their own study.
🔬Design:Araştırma Makalesi
📍Scope:60 sample
⚙️Variables:Monte-Carlo · Simulation · Bernoulli
Abstract
The aim of this study is to compare the robustness of Manova test statistics against the Type I error rate using the Monte Carlo simulation in Bernoulli and Uniform distribution. In the method, numbers have been 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 RStudio. The specified combinations have been repeated 10,000 times. As the result Pillai Trace test statistic has been the least deviating from the nominal α =0.05 value. Wilk Lambda and Hotelling-Lawley Trace test statistics results have been close to each other. Researchers can get help from these suggested results during their own study.
Koç, Ş., Çanga, D., Önem, A. B., Yavuz, E., Şahin, M. (2019). A Monte Carlo Simulation Study Robustness of Manova Test Statistics in Bernoulli and Uniform Distribution. Black Sea Journal of Engineering and Science, Cilt: 2 Sayı: 2, 42–51. https://ajindex.com/articles/1467524
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