134 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- United States Food and Drug AdministrationUS6 papers
- China Pharmaceutical UniversityCN2 papers
- Food and Drug AdministrationTH2 papers
- Harvard UniversityUS2 papers
- The University of Texas MD Anderson Cancer CenterUS2 papers
- University of California, BerkeleyUS2 papers
- University of WashingtonUS2 papers
- Bentley UniversityUS1 paper
- Brigham and Women's HospitalUS1 paper
- Center for Devices and Radiological HealthUS1 paper
- Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUS1 paper
- Eureka ScientificUS1 paper
10 papers
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…
Applications of Machine Learning in Pharmacogenomics: Clustering Plasma Concentration-Time Curves
Jackson P. Lautier, Stella Grosser, Jessica Kim +2
Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential for…
Learning diffusion coefficients, kinetic parameters, and the number of underlying states from a multi-state diffusion process: robustness results and application to PDK1/PKC, dynamics
Lewis R. Baker, Moshe T. Gordon, Brian P. Ziemba +3
Systems driven by Brownian motion are ubiquitous. A prevailing challenge is inferring, from data, the diffusion and kinetic parameters that describe these stochastic processes. In…
Practical considerations for specifying a super learner
Rachael V. Phillips, Mark J. van der Laan, Hana Lee +1
Common tasks encountered in epidemiology, including disease incidence estimation and causal inference, rely on predictive modeling. Constructing a predictive model can be thought o…
Optimal Bayesian hierarchical model to accelerate the development of tissue-agnostic drugs and basket trials
Liyun Jiang, Lei Nie, Fangrong Yan +1
Tissue-agnostic trials enroll patients based on their genetic biomarkers, not tumor type, in an attempt to determine if a new drug can successfully treat disease conditions based o…
Hi3+3: A Model-Assisted Dose-Finding Design Borrowing Historical Data
Yunshan Duan, Sue-Jane Wang, Yuan Ji
Background -- In phase I clinical trials, historical data may be available through multi-regional programs, reformulation of the same drug, or previous trials for a drug under the…
Elastic Priors to Dynamically Borrow Information from Historical Data in Clinical Trials
Liyun Jiang, Lei Nie, Ying Yuan
Use of historical data and real-world evidence holds great potential to improve the efficiency of clinical trials. One major challenge is how to effectively borrow information from…
Estimating and interpreting secondary attack risk: Binomial considered harmful
Yushuf Sharker, Eben Kenah
The household secondary attack risk (SAR), often called the secondary attack rate or secondary infection risk, is the probability of infectious contact from an infectious household…
The use of covariates and random effects in evaluating predictive biomarkers under a potential outcome framework
Zhiwei Zhang, Lei Nie, Guoxing Soon +1
Predictive or treatment selection biomarkers are usually evaluated in a subgroup or regression analysis with focus on the treatment-by-marker interaction. Under a potential outcome…
Accounting for Calibration Uncertainties in X-ray Analysis: Effective Areas in Spectral Fitting
Hyunsook Lee, Vinay L. Kashyap, David A. van Dyk +9
While considerable advance has been made to account for statistical uncertainties in astronomical analyses, systematic instrumental uncertainties have been generally ignored. This…