  Respondent-driven sampling (RDS) is a procedure to sample from hard-to-reach
populations. It has been widely used in several countries, especially in the
monitoring of HIV/AIDS and other sexually transmitted infections. Hard-to-reach
populations have had a key role in the dynamics of such epidemics and must
inform evidence-based initiatives aiming to curb their spread. In this paper,
we present a simple test for network dependence for a binary response variable.
We estimate the prevalence of the response variable. We also propose a binary
regression model taking into account the RDS structure which is included in the
model through a latent random effect with a correlation structure. The proposed
model is illustrated in a RDS study for HIV and Syphilis in men who have sex
with men implemented in Campinas (Brazil).
