
Mixed models for repeated measures should include timebycovariate interactions to assure power gains and robustness against dropout bias relative to completecase ANCOVA
In randomized trials with continuousvalued outcomes the goal is often t...
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Multivariate Probabilistic Regression with Natural Gradient Boosting
Many singletarget regression problems require estimates of uncertainty ...
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Designing efficient randomized trials: power and sample size calculation when using semiparametric efficient estimators
Trials enroll a large number of subjects in order to attain power, makin...
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Bayesian prognostic covariate adjustment
Historical data about disease outcomes can be integrated into the analys...
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Increasing the efficiency of randomized trial estimates via linear adjustment for a prognostic score
Estimating causal effects from randomized experiments is central to clin...
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Performance metrics for interventiontriggering prediction models do not reflect an expected reduction in outcomes from using the model
Clinical researchers often select among and evaluate risk prediction mod...
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A Causal Machine Learning Framework for Predicting Preventable Hospital Readmissions
Clinical predictive algorithms are increasingly being used to form the b...
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NGBoost: Natural Gradient Boosting for Probabilistic Prediction
We present Natural Gradient Boosting (NGBoost), an algorithm which bring...
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Generalpurpose validation and model selection when estimating individual treatment effects
Practitioners in medicine, business, political science, and other fields...
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SynthValidation: Selecting the Best Causal Inference Method for a Given Dataset
Many decisions in healthcare, business, and other policy domains are mad...
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Some methods for heterogeneous treatment effect estimation in highdimensions
When devising a course of treatment for a patient, doctors often have li...
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Alejandro Schuler
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