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09/14/2023
Choosing a Proxy Metric from Past Experiments
In many randomized experiments, the treatment effect of the long-term me...
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03/03/2023
Diagnosing Model Performance Under Distribution Shift
Prediction models can perform poorly when deployed to target distributio...
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05/21/2022
Bias-robust Integration of Observational and Experimental Estimators
We describe a simple approach for combining an unbiased and a (possibly)...
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03/24/2022
Calibration Error for Heterogeneous Treatment Effects
Recently, many researchers have advanced data-driven methods for modelin...
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03/23/2022
Causal Inference in High Dimensions – Without Sparsity
We revisit the classical causal inference problem of estimating the aver...
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11/15/2021
Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects
There are a number of available methods that can be used for choosing wh...
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06/30/2021
The MultiBERTs: BERT Reproductions for Robustness Analysis
Experiments with pretrained models such as BERT are often based on a sin...
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05/31/2021
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests
Informally, a `spurious correlation' is the dependence of a model on som...
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03/23/2021
SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression
Logistic regression remains one of the most widely used tools in applied...
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01/16/2021
Deep Cox Mixtures for Survival Regression
Survival analysis is a challenging variation of regression modeling beca...
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11/06/2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
ML models often exhibit unexpectedly poor behavior when they are deploye...
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06/24/2020
A Clinical Trial Derived Reference Set for Evaluating Observational Study Methods
Informing clinical practice in a learning health system requires good ca...
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03/12/2020
Off-policy Policy Evaluation For Sequential Decisions Under Unobserved Confounding
When observed decisions depend only on observed features, off-policy pol...
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12/15/2019
Estimation and Validation of a Class of Conditional Average Treatment Effects Using Observational Data
While sample sizes in randomized clinical trials are large enough to est...
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08/28/2018
Bounds on the conditional and average treatment effect in the presence of unobserved confounders
The causal effect of an intervention can not be consistently estimated w...
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04/11/2018