Distributions of zero-inflated models with application to HIV exposed infants
Nekesa, Faith Victory
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The instances of data with excess zeros are commonly found in many disciplines, including the public health. Several models have been proposed when analyzing this kind of data. The World Health Organization (WHO) indicates that majority of the 1.8 million children who are at the present with HIV in sub-Saharan Africa got the HIV virus from their mothers probably during delivery, pregnancy or through breastfeeding, but the study shows there is a drop in the rate of infections due to interventions that have been put in place. Here we attempt to fit zero-inflated models to data in this setting. The objective is to systematically compare distributions of the various zero-inflated models with an application to HIV Exposed Infants (HEI). We revisit zero-inflated models, conducted the simulations and applied the models to HEI data. The models performance were evaluated by Akaike Information Criteria(AIC).The simulation results indicated ZAP had the lowest AIC value of 467.95 at 80% of zeros. The real data showed ZAP as the best fit for the simulation data since it had the lowest AIC value. From the simulations results of the AIC value and the real data results, it is clear that ZAP is the best fitting model.