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05/18/2023
On true versus estimated propensity scores for treatment effect estimation with discrete controls
The finite sample variance of an inverse propensity weighted estimator i...
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09/23/2022
Feature selection in stratification estimators of causal effects: lessons from potential outcomes, causal diagrams, and structural equations
What is the ideal regression (if any) for estimating average causal effe...
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09/15/2022
Stochastic Tree Ensembles for Estimating Heterogeneous Effects
Determining subgroups that respond especially well (or poorly) to specif...
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08/21/2022
Statistical Aspects of SHAP: Functional ANOVA for Model Interpretation
SHAP is a popular method for measuring variable importance in machine le...
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04/23/2022
Local Gaussian process extrapolation for BART models with applications to causal inference
Bayesian additive regression trees (BART) is a semi-parametric regressio...
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06/18/2021
Bayesian decision theory for tree-based adaptive screening tests with an application to youth delinquency
Crime prevention strategies based on early intervention depend on accura...
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06/08/2021
Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis
It is widely speculated that auditors' public forecasts of bankruptcy ar...
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09/14/2020
Semi-supervised learning and the question of true versus estimated propensity scores
A straightforward application of semi-supervised machine learning to the...
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07/20/2020
Estimating heterogeneous effects of continuous exposures using Bayesian tree ensembles: revisiting the impact of abortion rates on crime
In estimating the causal effect of a continuous exposure or treatment, i...
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02/09/2020
Stochastic tree ensembles for regularized nonlinear regression
This paper develops a novel stochastic tree ensemble method for nonlinea...
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12/21/2019
A Symmetric Prior for Multinomial Probit Models
Under standard prior distributions, fitted probabilities from Bayesian m...
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05/23/2019
Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017
This brief note documents the data generating processes used in the 2017...
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10/04/2018
Accelerated Bayesian Additive Regression Trees
Although less widely known than random forests or boosted regression tre...
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09/25/2018
A Survey of Learning Causality with Data: Problems and Methods
The era of big data provides researchers with convenient access to copio...
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06/14/2018
Efficient sampling for Gaussian linear regression with arbitrary priors
This paper develops a slice sampler for Bayesian linear regression model...
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05/01/2014