When assessing causal effects, determining the target population to which the results are
intended to generalize is a critical decision. Randomized and observational studies each …

Great care is taken in epidemiologic studies to ensure the internal validity of causal effect
estimates; however, external validity has received considerably less attention. When the …

The ABCD study is a new and ongoing project of very substantial size and scale involving
21 data acquisition sites. It aims to recruit 11,500 children and follow them for ten years with …

An innovative and accessible guide to doing social research in the digital age. In just the
past several years, we have witnessed the birth and rapid spread of social media, mobile …

Statisticians are increasingly posed with thought-provoking and even paradoxical questions,
challenging our qualifications for entering the statistical paradises created by Big Data. By …

Although selecting a probability sample has been the standard for decades when making
inferences from a sample to a finite population, incentives are increasing to use …

ABCD is a longitudinal, observational study of US children, ages 9-10 at baseline, recruited
at random from the household populations in defined catchment areas for each of 21 study …

Self-selection into prospective cohort studies and loss to follow-up can cause biased
exposure-outcome association estimates. Previous investigations illustrated that such …

With increasing data availability, causal effects can be evaluated across different data sets,
both randomized controlled trials (RCTs) and observational studies. RCTs isolate the effect …

We consider methods for causal inference in randomized trials nested within cohorts of trial‐
eligible individuals, including those who are not randomized. We show how baseline …