Quantile Regression in Biostatistics

Jayabrata Biswas, Hemant Kulkarni and Kiranmoy Das
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Jayabrata Biswas: Interdisciplinary Statistical Research Unit, Indian Statistical Institute, India
Hemant Kulkarni: Human Genetics Unit, Indian Statistical Institute, India
Kiranmoy Das: Interdisciplinary Statistical Research Unit, Indian Statistical Institute, India

Biostatistics and Biometrics Open Access Journal, 2017, vol. 2, issue 5, 102-105

Abstract: Quantile regression has been a very effective modelling approach in many real applications. Unlike the mean regression, quantile regression focuses on modelling the entire distribution of the response variable, not just the mean value. We review some working models of quantile regression. We demonstrate some real applications of such modelling in Biostatistics and related disciplines. We also discuss some recent developments in modelling multiple responses in the context of quantile regression.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:2:y:2017:i:5:p:102-105

DOI: 10.19080/BBOAJ.2017.02.555596

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