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Comparing Welch ANOVA, a Kruskal-Wal...

Liu, Hangcheng.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance./
Author:	Liu, Hangcheng.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2015,
Description:	49 p.
Notes:	Source: Masters Abstracts International, Volume: 77-05.
Contained By:	Masters Abstracts International77-05.
Subject:	Biostatistics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1601507
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. - Ann Arbor : ProQuest Dissertations & Theses, 2015 - 49 p.

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

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

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.

ISBN: 9781339132600Subjects--Topical Terms:

1002712
Biostatistics.
Subjects--Index Terms:

ANOVA

Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance.
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245 1 0 $a Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2015
300 $a 49 p.
500 $a Source: Masters Abstracts International, Volume: 77-05.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Wan, Wen.
502 $a Thesis (M.S.)--Virginia Commonwealth University, 2015.
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.
590 $a School code: 2383.
650 4 $a Biostatistics. $3 1002712
653 $a ANOVA
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
690 $a 0308
710 2 $a Virginia Commonwealth University. $b Biostatistics. $3 3774427
773 0 $t Masters Abstracts International $g 77-05.
790 $a 2383
791 $a M.S.
792 $a 2015
793 $a English
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1601507