In this paper, we combine two methodologies used in the model-based survey sampling, namely the prediction of the finite population total, named T, under informative sampling and full response, see Sverchkov and Pfeffermann (2004), and the prediction of T with a noninformative sampling design...

In most surveys, the risk of nonresponse is a factor taken into account at the planning stage. Commonly, resources are set aside for a follow-up procedure which aims at reducing the nonresponse rate. However, we should pay attention to the effect of nonresponse, rather than the nonresponse rate...

In most surveys, the risk of nonresponse is a factor taken into account at the planning stage. Commonly, resources are set aside for a follow-up procedure which aims at reducing the nonresponse rate. However, we should pay attention to the effect of nonresponse, rather than the nonresponse rate...

We propose Bayesian methods with five types of priors to estimate cell probabilities in an incomplete multi-way contingency table under nonignorable nonresponse. In this situation, the maximum likelihood (ML) estimates often fall in the boundary solution, causing the ML estimates to become...

Good estimates of HIV prevalence are important for policy makers in order to plan control programs and interventions. Although population-based surveys are now considered the "gold standard" to monitor the HIV epidemic, they are usually plagued by problems of nonignorable nonresponse. This paper...

In many surveys, the goal is to estimate the proportion of the population with a certain characteristic of interest. This estimation problem is often complicated by survey nonresponse and the difficulty in modeling the nonresponse mechanism. In this paper, a new method is developed for analyzing...

This paper studies modeling of nonignorable nonresponse in panel surveys. A class of sequential conditional logistic models for nonresponse is considered. Model-based maximum likelihood estimation and imputation are used for estimating population proportions. Various models are evaluated, and...

This paper studies modeling of nonignorable nonresponse in panel surveys. A class of sequential conditional logistic models for nonresponse is considered. Model-based maximum likelihood estimation and imputation are used for estimating population proportions. Various models are evaluated, and...

In this paper we propose a general framework to deal with datasets where a binary outcome is subject to misclassification and, for some sampling units, neither the error-prone variable of interest nor the covariates are recorded. A model to describe the observed data is for-malized and eficient...