A Pairwise Likelihood Method for Survey Data with Sampling Weights Incorporated Under Two-Level Models

• Activity Number: 527 - New Approaches to Model-Assisted Survey Estimation with Informative Weights
• Type: Invited
• Date/Time: Thursday, August 6, 2020 : 1:00 PM to 2:50 PM
• Sponsor: Survey Research Methods Section
• Author(s): Grace Yi* and John N. K. Rao and Haocheng Li
• Companies: Unievrsity of Western Ontario and Carlton University and Roche Canada
• Keywords: Multi-level model; Pairwise likelihood; Inferential procedure

Abstract

Multi-level models provide a convenient framework for analyzing data from survey samples with hierarchical structures. Inferential procedures that take account of survey design features are well established for single-level (or marginal) models. On the other hand, available methods that are valid for general multi-level models are somewhat limited. In this talk, I will discuss a method for two-level models, based on a weighted pairwise likelihood approach, that takes account of design features and provides valid inferences even for small sample sizes within level 2 units.