Comparison of the Performance of Logistic Regression Model in the Presence and Absence of Mediation

Abstract

Over the last decade major global efforts mounted to address the HIV epidemic has realized notable successes in combating the pandemic. Sub Saharan Africa (SSA) still remains a global epicenter of the disease, accounting for more than 70% of the global burden of infections. Despite wide spread use of various intervention strategies that act as mediation factors in Human Immunodeficiency Virus (HIV) prevention, HIV prevalence still remains a challenge especially in some geographic areas and populations. Therefore, how mediation factors interact with the prevailing HIV risk factors to cause an impact on its prevalence remains a question not answered. This study considered Exposure to HIV related media as a mediator variable in the relationship between HIV risk factors and HIV prevalence. Two logistic regression models, one in presence of mediation and another in absence of mediation were formulated and compared to establish the best performing model. Models were fitted to real data from the Kenya Population-based HIV Impact Assessment survey-2018 and model parameters were estimated using Maximum Likelihood Estimation in R. Results based on both Akaike’s Information Criterion and the McFadden’s R² value revealed that the model formulated in presence of mediation performed better compared to that without mediation.