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dc.contributor.authorMola, Tilence
dc.contributor.authorMbete, Drinold Aluda
dc.contributor.authorSirengo, Job
dc.date.accessioned2025-08-25T10:22:00Z
dc.date.available2025-08-25T10:22:00Z
dc.date.issued2025-03-03
dc.identifier.urihttps://doi.org/10.18502/jbe.v11i1.19316
dc.identifier.urihttps://publish.kne-publishing.com/index.php/jbe/article/view/19316
dc.identifier.urihttp://ir-library.mmust.ac.ke:8080/xmlui/handle/123456789/3271
dc.description.abstractIntroduction: Estimating prevalence in cause-effect relationships where the mediator variables are assumed to be latent is not usually easy. However, the use of proper indicators and statistical model can make the measurement and use of such constructs easy. Methods: Structural Equation Modeling makes it possible to analyze simultaneously both the relationship between the latent variable and the links between the latent variable and their indicators. The 2018 Kenya AIDS Indicator Survey data was used to validate the model developed. The maximum likelihood was used to estimate the model parameters. The findings of the study were, there is a relationship between education attainment and knowledge /awareness of HIV/AIDS. Results: The results further shows that education levels are not associated with HIV prevalence after controlling for a number of socio-demographic characteristics and behavioral factors. Conclusion: These findings can inform policy makers in formulation of appropriate HIV/AIDS management (policies) and intervention strategies aimed at reducing HIV/AIDS prevalence that has remained a challenge in many developing countries.en_US
dc.language.isoenen_US
dc.publisherJournal of Biostatistics and Epidemiologyen_US
dc.subjectEstimation,HIV Prevalence, Among Women, Presence of Mediation, Latent Trait Analysisen_US
dc.titleEstimation of HIV Prevalence among Women in Kenya in the Presence of Mediation Using Latent Trait Analysisen_US
dc.typeArticleen_US


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