The linear model often serves as a starting point for applying statistics in psychology. Often,
formal training beyond the linear model is limited, creating a potential pedagogical gap …

Survey data in social, behavioral, and health sciences often contain many variables (p).
Structural equation modeling (SEM) is commonly used to analyze such data. With a …

Increasing floods and droughts are raising concerns of an accelerating water cycle,
however, the relative contributions to streamflow changes from climate and land …

Methods for cluster-robust inference are routinely used in economics and many other
disciplines. However, it is only recently that theoretical foundations for the use of these …

Cryptocurrency markets exhibit periods of large, recurrent arbitrage opportunities across
exchanges. These price deviations are much larger across than within countries, and …

We develop a framework for difference-in-differences designs with staggered treatment
adoption and heterogeneous causal effects. We show that conventional regression-based …

Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine
for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We …

I follow The Design of Experiments, using randomization statistical inference to test the null
hypothesis of no treatment effects in a comprehensive sample of 53 experimental papers …

We consider statistical inference for regression when data are grouped into clusters, with
regression model errors independent across clusters but correlated within clusters …

The increasingly visible presence of heavily armed police units in American communities
has stoked widespread concern over the militarization of local law enforcement. Advocates …