airpred: A Flexible R Package Implementing Methods for Predicting Air Pollution

no code implementations • 29 May 2018 • M. Benjamin Sabath, Qian Di, Danielle Braun, Joel Schwarz, Francesca Dominici, Christine Choirat

Fine particulate matter (PM$_{2. 5}$) is one of the criteria air pollutants regulated by the Environmental Protection Agency in the United States.

A Fast Divide-and-Conquer Sparse Cox Regression

2 code implementations • 2 Apr 2018 • Yan Wang, Nathan Palmer, Qian Di, Joel Schwartz, Isaac Kohane, Tianxi Cai

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$.

Computation Applications

Causal inference in the context of an error prone exposure: air pollution and mortality

1 code implementation • 2 Dec 2017 • Xiao Wu, Danielle Braun, Marianthi-Anna Kioumourtzoglou, Christine Choirat, Qian Di, Francesca Dominici

We propose a new approach for estimating causal effects when the exposure is measured with error and confounding adjustment is performed via a generalized propensity score (GPS).

Methodology Applications