Some theoretical and practical aspects of empirical likelihood methods for complex surveys. (English) Zbl 07767689
Summary: This paper provides an overview on two parallel approaches to design-based inference with complex survey data: the pseudo empirical likelihood methods and the sample empirical likelihood methods. The general framework covers parameters defined through smooth or non-differentiable estimating functions for analytic use of survey data as well as descriptive finite population parameters, and the theory focuses on point estimation, hypothesis tests and variable selection under an arbitrary sampling design. Major practical issues for the implementation of the methods, including computational algorithms, are briefly discussed. Results from simulation studies to compare the finite sample performances of the two approaches are presented.
{© 2018 The Authors. International Statistical Review © 2018 International Statistical Institute}
{© 2018 The Authors. International Statistical Review © 2018 International Statistical Institute}
MSC:
| 62Gxx | Nonparametric inference |
| 62Dxx | Statistical sampling theory and related topics |
| 62Jxx | Linear inference, regression |
Keywords:
design-based inference; estimating equations; hypothesis tests; pseudo empirical likelihood; sample empirical likelihood; variable selectionReferences:
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