activity
20152026
most citedTensor Completion for Causal Inference with Multivariate Longitudinal Data: A Reevaluation of COVID-19 Mandates

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

stat.AP2026

Scattered spring: How climate change disrupts the synchrony of biological events

Jonathan Auerbach, Andrew Gelman, E. M. Wolkovich

Many biological processes, including plant leafout and flowering, occur once cumulative temperatures reach a threshold, a relationship known as the thermal-sum model. In this way,…

stat.ME2022★ 1 cited

Tensor Completion for Causal Inference with Multivariate Longitudinal Data: A Reevaluation of COVID-19 Mandates

Jonathan Auerbach, Martin Slawski, Shixue Zhang

We propose a new method that uses tensor completion to estimate causal effects with multivariate longitudinal data, data in which multiple outcomes are observed for each unit and t…

stat.AP2018

Forecasting the Urban Skyline with Extreme Value Theory

Jonathan Auerbach, Phyllis Wan

The world's urban population is expected to grow fifty percent by the year 2050 and exceed six billion. The major challenges confronting cities, such as sustainability, safety, and…

stat.AP2017

A Hierarchical Bayes Approach to Adjust for Selection Bias in Before-After Analyses of Vision Zero Policies

Jonathan Auerbach, Christopher Eshleman, Rob Trangucci

American cities devote significant resources to the implementation of traffic safety countermeasures that prevent pedestrian fatalities. However, the before-after comparisons typic…

stat.AP2015

Age-aggregation bias in mortality trends

Andrew Gelman, Jonathan Auerbach

In a recent article in PNAS, Case and Deaton show a figure illustrating "a marked increase in the all-cause mortality of middle-aged white non-Hispanic men and women in the United…