SEMINAR by Jeffrey Näf (Institut national de recherche en sciences et technologies du numérique, INRIA) on "Imputation under Missing at Random: How to Impute and How to Evaluate Imputations"

Abstract :
In this workshop we take a deep dive into missing values from the standpoint of imputation. In the first part, I start by properly defining the problem of missingness and introducing a view on missing values that is particularly suited for imputation. Focussing on the missing at random (MAR) case, we discuss classical results of ignorability and what a good imputation method needs to bring to the table. Within this discussion, I also introduce some of the most promising imputation methods currently available. Finally, we take a brief look at state-of-the-art research on how to evaluate an imputation method for a given dataset, based on the concept of imputation scores (I-Scores). Throughout I provide examples to illustrate the concepts. If time allows, I will also discuss problems and approaches under the more difficult scenario of missing not at random (MNAR) missingness.
In the second part, we study the concepts introduced in the first part on tangible R examples.

This seminar will be accessible online via Teams