About the Short Course

Incorporating information from several sources is a fundamental problem in statistics. In statistical agencies, the desire to combine information from different sources to obtain an improved official statistic is increasing and survey data integration becomes an emerging area of research. In this short course, we review the current state-of-the-art survey data integration methods and discuss future research direction.

In-Person Event. Location Of Short Courses: University of Ottawa

Who is this course for?

Graduate students, researchers, and sampling statisticians in government agencies.

Level Of Instruction: Advanced

Learning Outcomes

Understanding on the theory and methods for data integration. Propensity score weighting, calibration weighting, empirical likelihood method, etc.

Course Materials

Lecture note will be given before the short course.

Delivery Structure

• Part 1: Survey data integration: Introduction (90 minutes)
• Part 2: Prediction model approach to survey data integration (90 minutes)
• Part 3: Weighting approach to Survey data integration (90 minutes)
• Part 4: Advanced topics in survey data integration (90 minutes)

About the instructor: Dr. Jae-kwang Kim

Dr. Jae-kwang Kim is a LAS dean’s professor in Department of Statistics at Iowa State University. He is a fellow of ASA and IMS. His research interest lies in survey sampling and analysis with missing data. He is an author of the book, entitled “Statistical Method for Handling Incomplete data (Second edition)”, co-authored with Jun Shao.

Affiliations: Department of Statistics, Iowa State University