Title: When Some Data are Missing: Foundations of Imputation Theory and Recent Developments 
Facilitator: David Haziza, Université de Montréal; david.haziza@umontreal.ca 

Dr. Haziza is Professor in the Department of Mathematics and Statistics at Université de Montréal. He is also a part-time consultant at Statistics Canada. His research interests include the treatment of missing survey data and robust estimation procedures in the presence of influential units.

Workshop Description: The most common way to treat item nonresponse in surveys is to construct one or more replacement values to fill in a missing value, a process known as imputation. Single imputation consists of replacing a missing value by a single replacement value, whereas multiple imputation uses two or more replacement values. In this workshop, we will review various imputation procedures used in National Statistical Offices as well as the properties of point and variance estimators in the presence of imputed survey data. The workshop will provide the participants with insights about new developments in the field. Several examples and simulation studies will be presented.