Household Surveys in Developing and Transition Countries: Design, Implementation and Analysis 1 Chapter 19 Statistical analysis of survey data James R. Chromy Research Triangle Institute Research Triangle Park, North Carolina, USA Savitri Abeyasekera The University of Reading Reading, UK Abstract 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 analyzing survey data and variances of survey estimates need to be computed in a manner that reflects the complex sample design. This 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” uses of survey data that can be used to examine relationships between survey variables, namely multiple linear regression models, logistic regression models and multi-level models. These models form a set of valuable tools for analyzing 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 modeling techniques and also provide guidance on the interpretation of the results. Key Words: complex survey design, analytic statistics, regression, logistic regression, hierarchical structures, multi-level modeling.