Handling Missing Data: Using Multiple Imputation in Stata


  • Rose Medeiros, StataCorp LLC

This course will cover the use of Stata to perform multiple-imputation analysis. Multiple imputation (MI) is a simulation-based technique for handling missing data. The course will provide a brief introduction to multiple imputation and will focus on how to perform MI in Stata using the mi command. The three stages of MI (imputation, complete-data analysis, and pooling) will be discussed in detail with accompanying Stata examples. Various imputation techniques will be discussed, including multivariate normal imputation (MVN) and multiple imputation using chained equations (MICE). Also, a number of examples demonstrating how to efficiently manage multiple imputed data within Stata will be provided. Linear and logistic regression analysis of multiply imputed data as well as several postestimation features will be presented.

Fee: Members = $1500; Non-members = $2800

Tags: missing data, multiple imputation, Stata

Course Sections

Section 1

Location: ICPSR -- Ann Arbor, MI

Date(s): August 6 - August 8

Time: 9:00 AM - 5:00 PM


  • Rose Medeiros, StataCorp LLC