Social scientists are now in an era of data abundance, and machine learning tools are
increasingly used to extract meaning from data sets both massive and small. We explain …

There is an ongoing debate in the survey research literature about whether and when
probability and nonprobability sample surveys produce accurate estimates of a larger …

Finite population inference is a central goal in survey sampling. Probability sampling is the
main statistical approach to finite population inference. Challenges arise due to high cost …

We consider integrating a non-probability sample with a probability sample which provides
high dimensional representative covariate information of the target population. We propose …

When individuals evaluate policies, they consider both the policy's content and its
endorsers. In this study, we investigate the conditions under which these sometimes …

Randomized trials have been the gold standard for assessing causal effects since their
introduction by Fisher in the 1920s, since they can eliminate both observed and unobserved …

In the November 2016 US presidential election, many state-level public opinion polls,
particularly in the Upper Midwest, incorrectly predicted the winning candidate. One leading …

The spread of misinformation and disinformation is an urgent global problem threatening
information quality. Third-party fact checking is widely used to mitigate its harmful effects …

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 …

Online surveys are increasingly common in social and health studies, as they provide fast
and inexpensive results in comparison to traditional ones. However, these surveys often …