Abstract:
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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.
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