A modification to Welch test statistic is proposed to test the equality of population means of various groups under a Weibull distribution. The proposed test statistic is simple and corresponds to the standard Welch test statistic in which the maximum likelihood mean and variance estimators are replaced with robust estimators based on quantile, quantile least square and repeated median. The influence function and breakdown point of these robust estimators are obtained to show their robustness properties. In the simulation study, various experimental designs are considered to evaluate the performance of proposed modified Welch classical ANOVA tests in terms of the type I-errors studies via simulation study.WoSScopu
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
This paper considers the problem of comparing several means under the one-way Analysis of Variance (...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
In calculating mean equality for two or more groups, Analysis of Variance (ANOVA) is a ...
Abstract. It is known that using the F test for testing the equality of means in a one-way ANOVA is ...
In testing equality of scale parameters of k Weibull populations with a common shape an ANOVA test i...
In this study, robust Brown-Forsythe and robust Modified Brown-Forsythe ANOVA tests are proposed to ...
The ANOVA-F test is the most popular and commonly used procedure for comparing J independent groups....
The ANOVA-F test is the most popular and commonly used procedure for comparing J independent groups....
Analysis of Variance (ANOVA) is a well-known method to test the equality of mean for two or more gro...
This paper conducts a simulation study of the effects of violating the ANOVA normality assumption in...
In this paper, we introduce an alternative to Yuen’s test for the comparison of several population t...
Traditional analysis-of-variance (ANOVA) is based on ‘normality’ and ‘homogeneity’ assumptions. If e...
Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for ...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
This paper considers the problem of comparing several means under the one-way Analysis of Variance (...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
In calculating mean equality for two or more groups, Analysis of Variance (ANOVA) is a ...
Abstract. It is known that using the F test for testing the equality of means in a one-way ANOVA is ...
In testing equality of scale parameters of k Weibull populations with a common shape an ANOVA test i...
In this study, robust Brown-Forsythe and robust Modified Brown-Forsythe ANOVA tests are proposed to ...
The ANOVA-F test is the most popular and commonly used procedure for comparing J independent groups....
The ANOVA-F test is the most popular and commonly used procedure for comparing J independent groups....
Analysis of Variance (ANOVA) is a well-known method to test the equality of mean for two or more gro...
This paper conducts a simulation study of the effects of violating the ANOVA normality assumption in...
In this paper, we introduce an alternative to Yuen’s test for the comparison of several population t...
Traditional analysis-of-variance (ANOVA) is based on ‘normality’ and ‘homogeneity’ assumptions. If e...
Analysis of variance (ANOVA) is a common use parametric method to test the differences in means for ...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...
This paper considers the problem of comparing several means under the one-way Analysis of Variance (...
Student's t-test and classical F-test ANOVA rely on the assumptions that two or more samples are ind...