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...

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...

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...

This paper proposes a simple and efficient estimation procedure for the model with non-ignorable missing data studied by Morikawa and Kim (2016). Their semiparametrically efficient estimator requires explicit non- parametric estimation and so suffers from the curse of dimensionality and requires...

This paper proposes a simple and efficient estimation procedure for the model with non-ignorable missing data studied by Morikawa and Kim (2016). Their semiparametrically efficient estimator requires explicit non- parametric estimation and so suffers from the curse of dimensionality and requires...