Multiple Imputation in Household Surveys using Stata
Missing data are a serious issue for the analysis of household data. In this course we will explore approaches for dealing with this matter, focusing particularly on multiple imputation. The course is designed to:
• Highlight why missing data are important
• Provide an overview of different methods for dealing with missing data, including weighting, simple imputations, and multiple imputation
• Introduce the Stata suite of multiple imputation tools
• Provide hands-on experience in analysing multiply imputed data, particularly in labour economics
• Show what can go wrong when imputation is done 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.
Dates: To be confirmed
Mode of Delivery: This course will run over three weeks via Zoom. Lecture sessions will take place on Mondays and Wednesdays from 14h00 to 17h00 (SAST) and Fridays from 14h00 to 15h30. Practical exercises will be set for each lecture with detailed instructions and should be attempted on your own before the debriefing sessions. Practical debriefing sessions will run on Tuesdays, Thursdays and Fridays from 15h30 to 16h30. Sessions will be recorded, so participants can review the material and course notes will be made available.
Course Instructors: Prof Martin Wittenberg, School of Economics and Director of DataFirst
Course Fees: R10 500.00. Partial scholarships are available to students.
*DataFirst reserves the right to postpone or cancel this course due to lack of demand.