Dealing with missing data in household surveys
Missing data are a serious issue for the analysis of household data. In this course, we will explore approaches for dealing with this matter. The course is designed to:
• Highlight why missing data are important
• Provide an overview of different methods for dealing with missing data, including weighting, different types of simple imputations, as well as multiple imputation
• Look at the implication of different approaches for the estimates of means, proportions and percentiles, as well as the accuracy of those estimates
• Show what can go wrong when missing data are handled badly
Prerequisites: Participants are expected to have a good grounding in multivariate analysis techniques (multiple regression, discrete choice models), handling of survey data and some experience with Stata. They will also need access to Stata software.
Dates: To be confirmed
Course Instructors: Prof Martin Wittenberg, School of Economics and Director of DataFirst
Course Fees: R7 000.00. Partial scholarships are available to students.
*DataFirst reserves the right to postpone or cancel this course due to lack of demand.