The fact that survey data are obtained from units selected with complex sample designs needs to be taken into account in the survey analysis: weights need to be used in analysing survey data and variances of survey estimates need to be computed in a manner that reflects the complex sample design. The present chapter outlines the development of weights and their use in computing survey estimates and provides a general discussion of variance estimation for survey data. It deals first with what are termed “descriptive” estimates, such as the totals, means and proportions that are widely used in survey reports. It then discusses three forms of “analytic”approaches to survey data that can be used to examine relationships between survey variables, namely, multiple linear regression models, logistic regression models and multilevel models. These models form a set of valuable tools for analysing the relationships between a key response variable and a number of other factors. In this chapter, we give examples to illustrate the use of these modelling techniques and also provide guidance on the interpretation of the results.
Statistical analysis of survey data
Chromy, J., & Abeyasekara, S. (2005). Statistical analysis of survey data. In Household Sample Surveys in Developing and Transition Countries New York, NY: United Nations.