***** Fuller Lecture *****

Speaker: Danny Pfeffermann, University of Southampton

Title: Statistical Inference under Nonignorable Sampling and Nonresponse - An Empirical Likelihood Approach

Abstract: When the sample selection probabilities and/or the response probabilities are related to a model outcome variable even after conditioning on the model covariates, the model holding for the observed data is different from the model holding in the population, resulting in biased inference if not accounted for properly. Accounting for sample selection bias is relatively simple because the sample selection probabilities are usually known. Accounting for nonignorable nonresponse is harder since the response probabilities are generally unknown.

In the seminar, I shall describe a new approach for modelling complex survey data, which accounts simultaneously for nonignorable sampling and nonresponse. The approach combines the nonparametric empirical likelihood with a parametric model for the response probabilities, which contains the outcome variable as one of the covariates. Combining the model holding for the responding units with the model for the response probabilities defines the model holding for the missing data, which is used for imputing them. Model testing will also be considered. I shall illustrate the performance of the proposed approach using simulated data and an application to a real data set.

Danny Pfeffermann, Arie Preminger and Moshe Feder

Biography: Danny Pfeffermann is Professor of Social Statistics at the University of Southampton, UK, and Professor Emeritus of Statistics at the Hebrew University of Jerusalem, Israel. Until recently, he served as the National Statistician and Director General of Israel's Central Bureau of Statistics.