Keywords: Anti-Retroviral Therapy, HiV, Joint modelling, Linear mixed model, Repeated measures.
Recent studies have adopted a joint modelling approach as a more robust technique in studying outcomes of interest simultaneously especially when the interest is in the association between two dependent variables. This has been necessitated by the fact that modelling such outcomes separately often leads to biased inferences due to existing possible correlations especially in medical studies. We obtain HiV data for each county from the Kenya government open data website for the year 2014 and visualize on each county the HIV infections on the Kenyan map. High infection incidences are observed for counties located in Nyanza province of Kenya. We further jointly model the two outcomes of interest using the linear mixed models approach for repeated measures to capture the correlation between the two outcomes for each county. Results indicate the infections are indeed correlated with significant predictors such as ART coverage, Adults and Children in need of ART etc. This forms the basis of our results presentation while demonstrating linear mixed modelling approach to account for such correlations. Insights developed from this study should interest the health practitioners & researchers