Reader reaction on the generalized Kruskal-Wallis test for genetic association studies incorporating group uncertainty

Baolin Wu; Weihua Guan

doi:10.1111/biom.12260

Reader reaction on the generalized Kruskal-Wallis test for genetic association studies incorporating group uncertainty

Baolin Wu
, Weihua Guan

Biostatistics

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

Acar and Sun (2013, Biometrics 69, 427-435) presented a generalized Kruskal-Wallis (GKW) test for genetic association studies that incorporated the genotype uncertainty and showed its robust and competitive performance compared to existing methods. We present another interesting way to derive the GKW test via a rank linear model.

Original language	English (US)
Pages (from-to)	556-557
Number of pages	2
Journal	Biometrics
Volume	71
Issue number	2
DOIs	https://doi.org/10.1111/biom.12260
State	Published - Jun 1 2015

Bibliographical note

Publisher Copyright:
© 2014, The International Biometric Society.

Keywords

Kruskal-Wallis test
Linear model
Score test
Wald test

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10.1111/biom.12260

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title = "Reader reaction on the generalized Kruskal-Wallis test for genetic association studies incorporating group uncertainty",

abstract = "Acar and Sun (2013, Biometrics 69, 427-435) presented a generalized Kruskal-Wallis (GKW) test for genetic association studies that incorporated the genotype uncertainty and showed its robust and competitive performance compared to existing methods. We present another interesting way to derive the GKW test via a rank linear model.",

keywords = "Kruskal-Wallis test, Linear model, Score test, Wald test",

author = "Baolin Wu and Weihua Guan",

note = "Publisher Copyright: {\textcopyright} 2014, The International Biometric Society.",

year = "2015",

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AU - Wu, Baolin

AU - Guan, Weihua

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N2 - Acar and Sun (2013, Biometrics 69, 427-435) presented a generalized Kruskal-Wallis (GKW) test for genetic association studies that incorporated the genotype uncertainty and showed its robust and competitive performance compared to existing methods. We present another interesting way to derive the GKW test via a rank linear model.

AB - Acar and Sun (2013, Biometrics 69, 427-435) presented a generalized Kruskal-Wallis (GKW) test for genetic association studies that incorporated the genotype uncertainty and showed its robust and competitive performance compared to existing methods. We present another interesting way to derive the GKW test via a rank linear model.

KW - Kruskal-Wallis test

KW - Linear model

KW - Score test

KW - Wald test

UR - https://www.scopus.com/pages/publications/84931323740

UR - https://www.scopus.com/pages/publications/84931323740#tab=citedBy

U2 - 10.1111/biom.12260

DO - 10.1111/biom.12260

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VL - 71

SP - 556

EP - 557

JO - Biometrics

JF - Biometrics

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ER -

Reader reaction on the generalized Kruskal-Wallis test for genetic association studies incorporating group uncertainty

Abstract

Bibliographical note

Keywords

Publisher link

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