2017 Best Student Paper Award of the Survey Methods Section
The Survey Methods Section is pleased to announce that Shixiao Zhang from University of Waterloo has won the 2017 best student paper award of $300 for his paper co-authored with Peisong Han from University of Michigan and Changbao Wu from University of Waterloo. The winning paper is entitled “A unified empirical likelihood approach to testing MCAR and subsequent estimation”. This award was open to all students who presented at the 2017 Annual Meeting of the Society in the area of survey methods. All papers submitted to the Proceedings of the Survey Methods Section can be found on the web page of the Survey Methods Section:
Here is the abstract of the winning paper:
For estimation with missing data, a crucial step is to determine if the data are missing completely at random (MCAR), in which case a complete-case analysis would suffice. Most existing tests for MCAR do not provide a method for subsequent estimation once the MCAR is rejected. In the setting of estimating the means of some response variables that are subject to missingness, we propose a unified approach to testing MCAR and the subsequent estimation. Upon rejecting MCAR, the same set of weights used for testing can then be used for estimation. The resulting estimators are consistent if the missingness of each response variable depends only on a set of fully observed auxiliary variables and the true outcome regression model is among the user specified functions for deriving the weights. The proposed procedure is based on the calibration idea from survey sampling literature and the empirical likelihood theory. Simulation results show that the proposed strategy performs well for both testing and subsequent estimation.