TITLE:
Logistic Regression Modelling for Complex Survey Data with an Application for Bed Net Use in Mozambique
AUTHORS:
Sheyla Rodrigues Cassy, Isabel Natário, M. Rosário Martins
KEYWORDS:
Survey Logistic Regression, Complex Samples, Bed Net, Malaria, DHS
JOURNAL NAME:
Open Journal of Statistics,
Vol.6 No.5,
October
24,
2016
ABSTRACT: Logistic Regression Models have been widely
used in many areas of research, namely in health sciences, to study risk
factors associated to diseases. Many population based surveys, such as
Demographic and Health Survey (DHS), are constructed assuming complex sampling,
i.e., probabilistic, stratified and multistage sampling, with unequal weights
in the observations; this complex design must be taken into account in order to
have reliable results. However, this very relevant issue usually is not well
analyzed in the literature. The aim of the study is to specify the logistic
regression model with complex sample design, and to demonstrate how to estimate
it using the R software survey package. More specifically, we used Mozambique
Demographic Health and Survey data 2011 (MDHS 2011) to illustrate how to
correct for the effect of sample design in the particular case of estimating
the risk factors associated to the probability of using mosquito bed nets. Our
results show that in the presence of complex sampling, appropriate methods must
be used both in descriptive and inferential statistics.