550 citations · 976 across the 12 of their papers we have counts for
12 papers
Algorithmic Changes Are Not Enough: Evaluating the Removal of Race Adjustment from the eGFR Equation
Marika M. Cusick, Glenn M. Chertow, Douglas K. Owens +2
Changing clinical algorithms to remove race adjustment has been proposed and implemented for multiple health conditions. Removing race adjustment from estimated glomerular filtrati…
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations
Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin +2
End-to-end learning of dynamical systems with black-box models, such as neural ordinary differential equations (ODEs), provides a flexible framework for learning dynamics from data…
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…
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid
Irina Degtiar, Tim Layton, Jacob Wallace +1
While much of the causal inference literature has focused on addressing internal validity biases, both internal and external validity are necessary for unbiased estimates in a targ…
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,…
A Review of Generalizability and Transportability
Irina Degtiar, Sherri Rose
When assessing causal effects, determining the target population to which the results are intended to generalize is a critical decision. Randomized and observational studies each h…
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…
Nonparametric Bayesian Instrumental Variable Analysis: Evaluating Heterogeneous Effects of Coronary Arterial Access Site Strategies
Samrachana Adhikari, Sherri Rose, Sharon-Lise Normand
Percutaneous coronary interventions (PCIs) are nonsurgical procedures to open blocked blood vessels to the heart, frequently using a catheter to place a stent. The catheter can be…
Limitations of P-Values and for Stepwise Regression Building: A Fairness Demonstration in Health Policy Risk Adjustment
Sherri Rose, Thomas G. McGuire
Stepwise regression building procedures are commonly used applied statistical tools, despite their well-known drawbacks. While many of their limitations have been widely discussed…