There are two different empirical likelihood approaches for complex sampling designs: the “pseudo-empirical likelihood ” introduced by Chen and Sitter (1999) and the “unequal probability empirical likelihood ” approach proposed by Berger and Torres (2014, 2016). Both approaches are described and reviewed critically. We do not pretend to give an exhaustive account of all the applications of empirical likelihood in survey sampling. This paper is an extended version of Berger (2018b).<br/
Data used in social, behavioural, health or biological sciences may have a hierarchical structure du...
We consider an empirical likelihood framework for inference for a statistical model based on an info...
The pursuit of accurate methods for generalizing attributes of a population from a sampled subset is...
There are two different empirical likelihood approaches for complex sampling designs: “pseudoempiric...
Survey data are often collected with unequal probabilities from a stratified population. We propose ...
Empirical likelihood is a non-parametric, likelihood-based inference approach. In the design-based e...
Modeling survey data often requires having the knowledge of design and weighting variables. With pub...
Survey data are often collected with unequal probabilities from a stratified population. In many mod...
Empirical likelihood is a popular tool for incorporating auxiliary information and constructing nonp...
The design-approach is evaluated, using a likelihood approach to survey sampling. It is argued that ...
The design-approach is evaluated, using a likelihood approach to survey sampling. It is argued that ...
A comparison is made of the two concepts, generalized likelihood (from Bjørnstad, 1996) and Royall's...
The parameter of interest considered is the unique solution to a set of estimating equations, such a...
When two surveys carried out separately in the same population have common variables, it might be de...
Data used in social, behavioural, health or biological sciences may have a hierarchical structure du...
Data used in social, behavioural, health or biological sciences may have a hierarchical structure du...
We consider an empirical likelihood framework for inference for a statistical model based on an info...
The pursuit of accurate methods for generalizing attributes of a population from a sampled subset is...
There are two different empirical likelihood approaches for complex sampling designs: “pseudoempiric...
Survey data are often collected with unequal probabilities from a stratified population. We propose ...
Empirical likelihood is a non-parametric, likelihood-based inference approach. In the design-based e...
Modeling survey data often requires having the knowledge of design and weighting variables. With pub...
Survey data are often collected with unequal probabilities from a stratified population. In many mod...
Empirical likelihood is a popular tool for incorporating auxiliary information and constructing nonp...
The design-approach is evaluated, using a likelihood approach to survey sampling. It is argued that ...
The design-approach is evaluated, using a likelihood approach to survey sampling. It is argued that ...
A comparison is made of the two concepts, generalized likelihood (from Bjørnstad, 1996) and Royall's...
The parameter of interest considered is the unique solution to a set of estimating equations, such a...
When two surveys carried out separately in the same population have common variables, it might be de...
Data used in social, behavioural, health or biological sciences may have a hierarchical structure du...
Data used in social, behavioural, health or biological sciences may have a hierarchical structure du...
We consider an empirical likelihood framework for inference for a statistical model based on an info...
The pursuit of accurate methods for generalizing attributes of a population from a sampled subset is...