A novel and mathematically rigorous framework for calculating cost-effectiveness when outcomes are uncertain and patients care about risk.

A presentation of generalized risk-adjusted cost-effectiveness (GRACE), an improvement upon traditional cost-effectiveness useful for predicting value of medical technology with uncertain outcomes.

Evaluates statistical methods for prediction and validation of survival models with high-dimensional real-world clinicogenomic data.

Describes an open source software package, hesim, developed by the authors for simulating the value of medical technologies.

Validation of a pathbreaking microsimulation model that predicts health outcomes for a representative sample of Americans.

A novel statistical approach to estimating real-world effectiveness outcomes from clinical trial efficacy data.