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Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance./
作者:	Liu, Hangcheng.
面頁冊數:	1 online resource (49 pages)
附註:	Source: Masters Abstracts International, Volume: 77-05.
Contained By:	Masters Abstracts International77-05.
標題:	Biostatistics. -
電子資源:	click for full text (PQDT)
ISBN:	9781339132600

Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance.
Liu, Hangcheng.

Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance. - 1 online resource (49 pages)

Source: Masters Abstracts International, Volume: 77-05.

Thesis (M.S.)--Virginia Commonwealth University, 2015.

Includes bibliographical references

Analysis of variance (ANOVA) is a robust test against the normality assumption, but it may be inappropriate when the assumption of homogeneity of variance has been violated. Welch ANOVA and the Kruskal-Wallis test (a non-parametric method) can be applicable for this case. In this study we compare the three methods in empirical type I error rate and power, when heterogeneity of variance occurs and find out which method is the most suitable with which cases including balanced/unbalanced, small/large sample size, and/or with normal/non-normal distributions.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9781339132600Subjects--Topical Terms:

783654
Biostatistics.
Subjects--Index Terms:

ANOVAIndex Terms--Genre/Form:

554714
Electronic books.

Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance.
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520 $a Analysis of variance (ANOVA) is a robust test against the normality assumption, but it may be inappropriate when the assumption of homogeneity of variance has been violated. Welch ANOVA and the Kruskal-Wallis test (a non-parametric method) can be applicable for this case. In this study we compare the three methods in empirical type I error rate and power, when heterogeneity of variance occurs and find out which method is the most suitable with which cases including balanced/unbalanced, small/large sample size, and/or with normal/non-normal distributions.
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653 $a Homogeneous/heterogeneous
653 $a Kruskal-Wallis
653 $a Monte Carlo simulations
653 $a Power
653 $a Three-group comparison
653 $a Type I error
653 $a Welch
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