20 citations
- University of WashingtonUS9 papers
- Fred Hutch Cancer CenterUS3 papers
- Harvard UniversityUS3 papers
- Brigham and Women's HospitalUS2 papers
- Cancer Research And BiostatisticsUS2 papers
- Kaiser PermanenteUS2 papers
- McGill UniversityCA2 papers
- University of California, BerkeleyUS2 papers
- Bordeaux Population HealthFR1 paper
- Carnegie Mellon UniversityUS1 paper
- Center for Drug Evaluation and ResearchUS1 paper
- HealthPartnersUS1 paper
12 papers
Behavior of prediction performance metrics with rare events
Emily Minus, R. Yates Coley, Susan M. Shortreed +1
Objective: Area under the receiving operator characteristic curve (AUC) is commonly reported alongside prediction models for binary outcomes. Recent articles have raised concerns t…
Assessing treatment effects in observational data with missing confounders: A comparative study of practical doubly-robust and traditional missing data methods
Brian D. Williamson, Chloe Krakauer, Eric Johnson +13
In pharmacoepidemiology, safety and effectiveness are frequently evaluated using readily available administrative and electronic health records data. In these settings, detailed co…
AI-Assisted Causal Pathway Diagram for Human-Centered Design
Ruican Zhong, Donghoon Shin, Rosemary Meza +3
This paper explores the integration of causal pathway diagrams (CPD) into human-centered design (HCD), investigating how these diagrams can enhance the early stages of the design p…
Practical considerations for variable screening in the super learner
Brian D. Williamson, Drew King, Ying Huang
Estimating a prediction function is a fundamental component of many data analyses. The super learner ensemble, a particular implementation of stacking, has desirable theoretical pr…
Inference on summaries of a model-agnostic longitudinal variable importance trajectory with application to suicide prevention
Brian D. Williamson, Erica E. M. Moodie, Gregory E. Simon +2
Risk of suicide attempt varies over time. Understanding the importance of risk factors measured at a mental health visit can help clinicians evaluate future risk and provide approp…
Causal Quantile Treatment Effects with missing data by double-sampling
Shuo Sun, Sebastien Haneuse, Alexander W. Levis +5
Causal weighted quantile treatment effects (WQTE) are a useful complement to standard causal contrasts that focus on the mean when interest lies at the tails of the counterfactual…