The paper considers model-based inference for finite population parameters under informative sampling, when the draws of the different units are not independent and the joint selection probability is modeled using a copula. We extend the “sample likelihood” approach to the case of dependent draws and provide the expression of the likelihood given the selected sample, called here “selection likelihood”. We show how to derive maximum likelihood estimators of the model parameters based on the resulting selection likelihood. Further, we find optimal predictors of individual values and of finite population parameters under the proposed informative selection models. In an experiment based on the 1988 U.S. National Maternal and Infant Health Surve...
When the probabilities of selecting the individuals for the sample depend on the outcome values, we...
When the probabilities of selecting the individuals for the sample depend on the outcome values, we...
We argue that the conditional bias associated with a sample unit can be a useful measure of influenc...
The paper considers model-based inference for finite population parameters under informative samplin...
The paper considers model-based inference for finite population parameters under informative samplin...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
In this research we will deal with the problem of Bayes estimation of the parameter that characteris...
We have considered the problem in which a biased sample is selected from a finite population, and th...
This dissertation develops new model-based approaches for analysis of sample survey data. The main f...
This dissertation develops new model-based approaches for analysis of sample survey data. The main f...
In this research we will deal with the problem of Bayes estimation of the parameter that characteris...
When the probabilities of selecting the individuals for the sample depend on the outcome values, we...
When the probabilities of selecting the individuals for the sample depend on the outcome values, we...
We argue that the conditional bias associated with a sample unit can be a useful measure of influenc...
The paper considers model-based inference for finite population parameters under informative samplin...
The paper considers model-based inference for finite population parameters under informative samplin...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
International audienceInference for the parametric distribution of a response given covariates is co...
In this research we will deal with the problem of Bayes estimation of the parameter that characteris...
We have considered the problem in which a biased sample is selected from a finite population, and th...
This dissertation develops new model-based approaches for analysis of sample survey data. The main f...
This dissertation develops new model-based approaches for analysis of sample survey data. The main f...
In this research we will deal with the problem of Bayes estimation of the parameter that characteris...
When the probabilities of selecting the individuals for the sample depend on the outcome values, we...
When the probabilities of selecting the individuals for the sample depend on the outcome values, we...
We argue that the conditional bias associated with a sample unit can be a useful measure of influenc...