This bachelor’s thesis focuses on the effect of outliers on the one-way analysis of variance and examines whether the estimate in ANOVA is robust and whether the actual test itself is robust from influence of extreme outliers. The robustness of the estimates is examined using the breakdown point while the robustness of the test is examined by simulating the hypothesis test under some extreme situations. This study finds evidence that the estimates in ANOVA are sensitive to outliers, i.e. that the procedure is not robust. Samples with a larger portion of extreme outliers have a higher type-I error probability than the expected level
This article addresses the issue of building regression models for bounded responses, which are robu...
The Hat (H) matrix and in particular the elements of its principal diagonal (leverages) have a param...
The effect of outliers on reaction time analyses is evaluated. The first section assesses the power ...
This bachelor’s thesis focuses on the effect of outliers on the one-way analysis of variance and exa...
Analysis of Variance (ANOVA) techniques which is based on classical Least Squares (LS) method requir...
After much exertion and care to run an experiment in social science, the analysis of data should not...
The bachelor thesis focuses on the One-way ANOVA and its nonparametric counterpart the Kruskal-Walli...
The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined a...
A Monte Carlo simulation study was conducted to examine outliers’ influence on Type I error rates in...
Outliers are sample values that cause surprise in relation to the majority of the sample. This is no...
This study attempts to investigate the effect of outliers on estimation of parameters in regression ...
Analysis of Variance (ANOVA) is a well-known method to test the equality of mean for two or more gro...
We discuss the use of robust analysis of variance (ANOVA) techniques as applied to quality engineeri...
This monograph presents the work on robust procedures when researchers faced with data that appear t...
Traditional analysis-of-variance (ANOVA) is based on ‘normality’ and ‘homogeneity’ assumptions. If e...
This article addresses the issue of building regression models for bounded responses, which are robu...
The Hat (H) matrix and in particular the elements of its principal diagonal (leverages) have a param...
The effect of outliers on reaction time analyses is evaluated. The first section assesses the power ...
This bachelor’s thesis focuses on the effect of outliers on the one-way analysis of variance and exa...
Analysis of Variance (ANOVA) techniques which is based on classical Least Squares (LS) method requir...
After much exertion and care to run an experiment in social science, the analysis of data should not...
The bachelor thesis focuses on the One-way ANOVA and its nonparametric counterpart the Kruskal-Walli...
The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined a...
A Monte Carlo simulation study was conducted to examine outliers’ influence on Type I error rates in...
Outliers are sample values that cause surprise in relation to the majority of the sample. This is no...
This study attempts to investigate the effect of outliers on estimation of parameters in regression ...
Analysis of Variance (ANOVA) is a well-known method to test the equality of mean for two or more gro...
We discuss the use of robust analysis of variance (ANOVA) techniques as applied to quality engineeri...
This monograph presents the work on robust procedures when researchers faced with data that appear t...
Traditional analysis-of-variance (ANOVA) is based on ‘normality’ and ‘homogeneity’ assumptions. If e...
This article addresses the issue of building regression models for bounded responses, which are robu...
The Hat (H) matrix and in particular the elements of its principal diagonal (leverages) have a param...
The effect of outliers on reaction time analyses is evaluated. The first section assesses the power ...