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Found 6 papers, 4 papers with code
Heterogeneous Distributed Lag Models to Estimate Personalized Effects of Maternal Exposures to Air Pollution
A common goal is to identify critical windows of susceptibility--periods during gestation with increased association between maternal exposures and a future outcome.
Reflection on modern methods: Good practices for applied statistical learning in epidemiology
Statistical learning (SL) includes methods that extract knowledge from complex data.
Applications
Accurate Uncertainty Estimation and Decomposition in Ensemble Learning
We introduce a Bayesian nonparametric ensemble (BNE) approach that augments an existing ensemble model to account for different sources of model uncertainty.
Matching on Generalized Propensity Scores with Continuous Exposures
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
Adaptive and Calibrated Ensemble Learning with Dependent Tail-free Process
Ensemble learning is a mainstay in modern data science practice.
Causal inference in the context of an error prone exposure: air pollution and mortality
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
