Oguz Alper, Melike and Berger, Yves G. (2016) Modelling complex survey data with population level information: an empirical likelihood approach. Biometrika, 103 (2), 447-459. (doi:10.1093/biomet/asw014).
Abstract
Survey data are often collected with unequal probabilities from a stratified population. In many modelling situations, the parameter of interest is a subset of a set of parameters, with the others treated as nuisance parameters. We show that in this situation the empirical likelihood ratio statistic follows a chi-squared distribution asymptotically, under stratified single and multi-stage unequal probability sampling, with negligible sampling fractions. Simulation studies show that the empirical likelihood confidence interval may achieve better coverages and has more balanced tail error rates than standard approaches, which involve variance estimation, linearization or resampling.
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- Faculties (pre 2018 reorg) > Faculty of Social, Human and Mathematical Sciences (pre 2018 reorg) > Statistical Sciences Research Institute (S3RI) (pre 2018 reorg)
- Faculties (pre 2018 reorg) > Faculty of Social, Human and Mathematical Sciences (pre 2018 reorg) > Social Sciences (pre 2018 reorg)
Current Faculties > Faculty of Social Sciences > School of Economic Social and Political Science > Social Sciences (pre 2018 reorg)
School of Economic Social and Political Science > Social Sciences (pre 2018 reorg) - Current Faculties > Faculty of Social Sciences > School of Economic Social and Political Science > Social Statistics and Demography
School of Economic Social and Political Science > Social Statistics and Demography
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