Abstract:
Multilevel models take into account various degrees of aggregation in the
data. This study aims to bring together multilevel models from both frequentist
and Bayesian perspectives in identifying determinants of contraceptive
choices. The study uses the data from the 2016 South African Demographic
and Health Survey (SADHS). To analyse the dataset, a multinomial
logistic regression model has been used, model parameters were estimated
in SPSS for frequentist models. The Bayesian analyses with non informative
priors were strengthened by the use of the state of the art Hamiltonian
Monte Carlo algorithm (HMC), as implemented in the RStan package in
the R statistical software. The Bayesian nal model was selected based on
Watanabe{Akaike information criterion (WAIC), which has been shown to
outperform conventional information-criterion such as DIC. The results established
that an individual woman's choice of contraception is a function of
both individual characteristics and community e ects. In bivariate analysis,
injections showed a continued dominance as a preferred choice in SA. Community
level education was the most useful determinant of contraceptive
choices. Thus, this study recommends that Empowering woman through
education, will have a positive e ect on overall contraceptive prevalence.
