8 papers
Why Machine Learning Cannot Ignore Maximum Likelihood Estimation
Mark J. van der Laan, Sherri Rose
The growth of machine learning as a field has been accelerating with increasing interest and publications across fields, including statistics, but predominantly in computer science…
Identifying Undercompensated Groups Defined By Multiple Attributes in Risk Adjustment
Anna Zink, Sherri Rose
Risk adjustment in health care aims to redistribute payments to insurers based on costs. However, risk adjustment formulas are known to underestimate costs for some groups of patie…
Considerations Across Three Cultures: Parametric Regressions, Interpretable Algorithms, and Complex Algorithms
Ani Eloyan, Sherri Rose
We consider an extension of Leo Breiman's thesis from "Statistical Modeling: The Two Cultures" to include a bifurcation of algorithmic modeling, focusing on parametric regressions,…
Ethical Machine Learning in Health Care
Irene Y. Chen, Emma Pierson, Sherri Rose +3
The use of machine learning (ML) in health care raises numerous ethical concerns, especially as models can amplify existing health inequities. Here, we outline ethical consideratio…
Fair Regression for Health Care Spending
Anna Zink, Sherri Rose
The distribution of health care payments to insurance plans has substantial consequences for social policy. Risk adjustment formulas predict spending in health insurance markets in…
Consistent Estimation of Propensity Score Functions with Oversampled Exposed Subjects
Sherri Rose
Observational cohort studies with oversampled exposed subjects are typically implemented to understand the causal effect of a rare exposure. Because the distribution of exposed sub…