no code implementations • 21 Dec 2023 • Ellen M. Considine, Rachel C. Nethery, Gregory A. Wellenius, Francesca Dominici, Mauricio Tec
First, we introduce a novel RL environment enabling the evaluation of the effectiveness of heat alert policies to reduce heat-related hospitalizations.
1 code implementation • 1 Dec 2023 • Mauricio Tec, Ana Trisovic, Michelle Audirac, Sophie Woodward, Jie Kate Hu, Naeem Khoshnevis, Francesca Dominici
Spatial confounding poses a significant challenge in scientific studies involving spatial data, where unobserved spatial variables can influence both treatment and outcome, possibly leading to spurious associations.
no code implementations • 6 Feb 2023 • Mauricio Tec, Oladimeji Mudele, Kevin Josey, Francesca Dominici
Motivated by a key policy-relevant question in public health, we develop a neural network method and its theoretical underpinnings to estimate SRFs with robustness and efficiency guarantees.
no code implementations • 18 Sep 2020 • Falco J. Bargagli-Stoffi, Riccardo Cadei, Kwonsang Lee, Francesca Dominici
Estimation of subgroup-specific causal effects is performed via a two-stage approach for which we provide theoretical guarantees.
1 code implementation • 17 Dec 2018 • Xiao Wu, Fabrizia Mealli, Marianthi-Anna Kioumourtzoglou, Francesca Dominici, Danielle Braun
We apply our proposed method to estimate the average causal exposure-response function between long-term PM$_{2. 5}$ exposure and all-cause mortality among 68. 5 million Medicare enrollees, 2000-2016.
Methodology Applications
no code implementations • NeurIPS 2018 • Fei Jiang, Guosheng Yin, Francesca Dominici
Based on non-local prior distributions, we propose a Bayesian model selection (BMS) procedure for boundary detection in a sequence of data with multiple systematic mean changes.
1 code implementation • 14 Nov 2018 • Rachel C. Nethery, Yue Yang, Anna J. Brown, Francesca Dominici
We overcome the second challenge by developing a Bayesian hierarchical model that borrows information from other sources to impute cancer incidence at the desired finer level of spatial aggregation.
Methodology Applications
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.
3 code implementations • 4 Jan 2018 • Aaron Fisher, Cynthia Rudin, Francesca Dominici
Expanding on MR, we propose Model Class Reliance (MCR) as the upper and lower bounds on the degree to which any well-performing prediction model within a class may rely on a variable of interest, or set of variables of interest.
Methodology
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
1 code implementation • 25 Apr 2017 • Joseph Antonelli, Giovanni Parmigiani, Francesca Dominici
In observational studies, estimation of a causal effect of a treatment on an outcome relies on proper adjustment for confounding.
Methodology