Non-probability samples provide a challenging source of information for official statistics, because the data generating mechanism is unknown. Making inference from such samples therefore requires a ...

Survey sampling and estimation methods form the cornerstone of modern statistical inference, underpinning research across the social, medical, and natural sciences. At their heart, these methods ...

Social and economic scientists are tempted to use emerging data sources like big data to compile information about finite populations as an alternative for traditional survey samples. These data ...

Statistics are often estimated from a sample rather than from the entire population. If the inclusion probability of the sample is unknown to the researcher, that is, a nonprobability sample, naively ...

This repository presents a methodological framework for constructing individual prediction intervals over a finite population using data obtained from both probability and non-probability samples. The ...