20 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- 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
- University of MichiganUS2 papers
- University of PennsylvaniaUS2 papers
- Bordeaux Population HealthFR1 paper
- Carnegie Mellon UniversityUS1 paper
13 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…
An Application of the Causal Roadmap in Two Safety Monitoring Case Studies: Covariate-Adjustment and Outcome Prediction using Electronic Health Record Data
Brian D Williamson, Richard Wyss, Elizabeth A Stuart +4
Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these set…
Analysis of the 24-Hour Activity Cycle: An illustration examining the association with cognitive function in the Adult Changes in Thought (ACT) Study
Yinxiang Wu, Dori E. Rosenberg, Mikael Anne Greenwood-Hickman +7
The 24-hour activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach captures the interrelatedness of the daily time s…
Flexible variable selection in the presence of missing data
B. D. Williamson, Y. Huang
In many applications, it is of interest to identify a parsimonious set of features, or panel, from multiple candidates that achieves a desired level of performance in predicting a…
Optimal Multi-Wave Validation of Secondary Use Data with Outcome and Exposure Misclassification
Sarah C. Lotspeich, Gustavo G. C. Amorim, Pamela A. Shaw +2
The growing availability of observational databases like electronic health records (EHR) provides unprecedented opportunities for secondary use of such data in biomedical research.…
Accounting for spatial confounding in epidemiological studies with individual-level exposures: An exposure-penalized spline approach
Jennifer F. Bobb, Maricela F. Cruz, Stephen J. Mooney +3
In the presence of unmeasured spatial confounding, spatial models may actually increase (rather than decrease) bias, leading to uncertainty as to how they should be applied in prac…
Variable Selection in Regression-based Estimation of Dynamic Treatment Regimes
Zeyu Bian, Erica EM Moodie, Susan M Shortreed +1
Dynamic treatment regimes (DTRs) consist of a sequence of decision rules, one per stage of intervention, that finds effective treatments for individual patients according to patien…
Multiply Robust Causal Inference with Double Negative Control Adjustment for Categorical Unmeasured Confounding
Xu Shi, Wang Miao, Jennifer C. Nelson +1
Unmeasured confounding is a threat to causal inference in observational studies. In recent years, use of negative controls to mitigate unmeasured confounding has gained increasing…