A weighted bootstrap approach to logistic regression modelling in identifying risk behaviours associated with sexual activity

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dc.contributor.authorBrydon, Humphrey
dc.contributor.authorBlignaut, Rénette
dc.contributor.authorJacobs, Joachim
dc.date.accessioned2023-03-08T13:20:05Z
dc.date.available2023-03-08T13:20:05Z
dc.date.issued2019
dc.description.abstractThe latest population estimates released by Statistics South Africa indicate that 25.03% of alldeaths in 2017 in South Africa were AIDS-related. Along with these results, it is also reportedthat 7.06% of the population were living with HIV, with the HIV-prevalence among youth(aged 15–24) at 4.64% for 2017 (STATSSA. (2018). Retrieved from Statistics South Africa:http://www.statssa.gov.za/publications/P0302/P03022017.pdf). The data used in the studycontained information related to the risk-taking behaviours associated with the sexualactivity of enteringfirst-year students at the University of the Western Cape. In this study, alogistic regression modelling procedure was carried out on those students that weredetermined to be sexually active, therefore, in the modelling procedure significant riskbehaviours of sexually activefirst-year students could be identified. Of the 14 variablesincluded in the modelling procedure, six were found to be significantly associated withsexually active students.en_US
dc.identifier.citationBrydon, H. et al. (2019). A weighted bootstrap approach to logistic regression modelling in identifying risk behaviours associated with sexual activity. SAHARA-J: Journal of Social Aspects of HIV/AIDS, 16 (1) , pp.62-69. https://doi.org/10.1080/17290376.2019.1636708en_US
dc.identifier.issn1813-4424
dc.identifier.urihttps://doi.org/10.1080/17290376.2019.1636708
dc.identifier.urihttp://hdl.handle.net/10566/8560
dc.language.isoenen_US
dc.publisherTaylor and Francis Groupen_US
dc.subjectSexuality educationen_US
dc.subjectHIVen_US
dc.subjectPublic healthen_US
dc.subjectSouth Africaen_US
dc.subjectYouthen_US
dc.titleA weighted bootstrap approach to logistic regression modelling in identifying risk behaviours associated with sexual activityen_US
dc.typeArticleen_US

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