Title:
On the Use of a Logistic Regression Model in the Gene-Environment Problem: A Bayesian Approach

dc.contributor.authorAkanksha Gupta
dc.contributor.authorS.K. Upadhyay
dc.date.accessioned2026-02-07T09:04:14Z
dc.date.issued2019
dc.description.abstractSYNOPTIC ABSTRACT: The article provides the Bayes analysis of case-control data related to growth of cancerous cells in a reproductive organ of women. It is claimed that such cancerous growth may occur because of genes and environmental effects, the latter may be categorized as some personal practices, food and drinking habits, etc. The present work considers the logistic regression model with a number of genetic and environmental covariates to analyze such a data set. The ultimate aim of the study is to see if there is any association between gene and environmental components in the development of the disease. Some comments are also made to simplify the proposed logistic regression model by looking at appropriate variable selections using an important tool of Bayesian paradigm. Numerical results based on a real data set are provided for illustration purposes. © 2019, © 2019 Taylor & Francis Group, LLC.
dc.identifier.doi10.1080/01966324.2019.1570406
dc.identifier.issn1966324
dc.identifier.urihttps://doi.org/10.1080/01966324.2019.1570406
dc.identifier.urihttps://dl.bhu.ac.in/bhuir/handle/123456789/33341
dc.publisherTaylor and Francis Ltd.
dc.subjectCase-control study
dc.subjectgene-environment interaction
dc.subjectlogistic regression
dc.subjectretrospective analysis
dc.titleOn the Use of a Logistic Regression Model in the Gene-Environment Problem: A Bayesian Approach
dc.typePublication
dspace.entity.typeArticle

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