This work illustrates the joint use of a pilot study and an administrative data base for designing a probabilistic sample for an epidemiological survey. The target is to estimate the prevalence of an asymptomatic disease, the aortic valve stenosis (AS), in the elderly population of the city of...

This work illustrates the joint use of a pilot study and an administrative data base for designing a probabilistic sample for an epidemiological survey. The target is to estimate the prevalence of an asymptomatic disease, the aortic valve stenosis (AS), in the elderly population of the city of...

Young Lives is a longitudinal research project investigating the changing nature of childhood poverty. The study is tracking the development of 12,000 children in Ethiopia, Peru, India (Andhra Pradesh) and Vietnam through qualitative and quantitative research over a 15-year period. Since 2002,...

The quintile share ratio of disposable income is the primary inequality indicator of the European Union. As an inequality indicator, it must be sensitive to extreme large observations. Therefore, outliers have a strong impact on the bias and the variance of the classical quintile share ratio...

Random route samples are widely used in face-to-face surveys. Most previous studies of random route sample quality compare the data collected by random route samples with data from reliable sources, such as the German Microcensus. While these studies usually find few differences in the...

The use of hierarchical Bayesian spatial models in the analysis of ecological data is increasingly prevalent. The implementation of these models has been heretofore limited to specifically written software that required extensive programming knowledge to create. The advent of WinBUGS provides...

The estimation of a mean of a proportion is a frequent task in statistical survey analysis, and often such ratios are estimated from compositions such as income components, wage components, tax components, etc. In practice, the weighted arithmetic mean is regularly used to estimate the center of...

Multiple imputation is a method specifically designed for variance estimation in the presence of missing data. Rubin's combination formula requires that the imputation method is "proper" which essentially means that the imputations are random draws from a posterior distribution in a Bayesian...

Multiple imputation is a method specifically designed for variance estimation in the presence of missing data. Rubin’s combination formula requires that the imputation method is “proper” which essentially means that the imputations are random draws from a posterior distribution in a...