Selection bias poses a substantial challenge to valid statistical inference in nonprobability
samples. This study compared estimates of the first-dose COVID-19 vaccination rates …

This is a case study comparing outcomes for a probability‐based representative sample
versus a non‐probability convenience sample for the valuation of beach condition …

Introduction: Social capital, the effective functioning of social groups through networks of
relationships, can affect mental health and may be affected by COVID-19. We aimed to …

Randomized trials are considered the gold standard for estimating causal effects. Trial
findings are often used to inform policy and programming efforts, yet their results may not …

Morris Hansen made seminal contributions to the early development of sampling theory,
including convincing government survey administrators to use probability sampling as …

In 2019, a group of computer and social scientists began a project to converge these
disciplines, with the aim of harnessing data from social media to improve our understanding …

Recently, attention was drawn to the failure of two very large internet-based probability
surveys to correctly estimate COVID-19 vaccine uptake in the US in early 2021. Both the …

Fast online surveys without sampling frames are becoming increasingly important in survey
research. Their recruitment methods result in non‐probability samples. As the mechanism of …

Among the numerous explanations that have been offered for recent errors in pre-election
polls, selection bias due to non-ignorable partisan nonresponse bias, where the probability …

Bailey (2023a) does a very useful service to the polling and broader survey sampling
communities by highlighting the insights that the Meng (2018) equation provides into current …