25 citations · 32 across the 8 of their papers we have counts for
10 papers
Empirical Validation of a New Data Product from the Interstellar Boundary Explorer Satellite
Kelly R. Moran, Dave Osthus, Brian P. Weaver +4
Since 2008, the Interstellar Boundary Explorer (IBEX) satellite has been gathering data on heliospheric energetic neutral atoms (ENAs) while being exposed to various sources of bac…
Statistical methods for partitioning ribbon and globally-distributed flux using data from the Interstellar Boundary Explorer
Lauren J. Beesley, Dave Osthus, Kelly R. Moran +9
NASA's Interstellar Boundary Explorer (IBEX) satellite collects data on energetic neutral atoms (ENAs) that can provide insight into the heliosphere boundary between our solar syst…
Towards Improved Heliosphere Sky Map Estimation with Theseus
Dave Osthus, Brian P. Weaver, Lauren J. Beesley +5
The Interstellar Boundary Explorer (IBEX) satellite has been in orbit since 2008 and detects energy-resolved energetic neutral atoms (ENAs) originating from the heliosphere. Differ…
Addressing delayed case reporting in infectious disease forecast modeling
Lauren J Beesley, Dave Osthus, Sara Y Del Valle
Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future an…
Reconstructing magnetic deflections from sets of proton images using differential evolution
Joseph M. Levesque, Lauren J. Beesley
Proton imaging is a powerful technique for imaging electromagnetic fields within an experimental volume, in which spatial variations in proton fluence are a result of deflections t…
Multiple imputation with missing data indicators
Lauren J Beesley, Irina Bondarenko, Michael R Elliott +3
Multiple imputation is a well-established general technique for analyzing data with missing values. A convenient way to implement multiple imputation is sequential regression multi…
Accounting for not-at-random missingness through imputation stacking
Lauren J Beesley, Jeremy M G Taylor
Not-at-random missingness presents a challenge in addressing missing data in many health research applications. In this paper, we propose a new approach to account for not-at-rando…
Patient Recruitment Using Electronic Health Records Under Selection Bias: a Two-phase Sampling Framework
Guanghao Zhang, Lauren J. Beesley, Bhramar Mukherjee +1
Electronic health records (EHRs) are increasingly recognized as a cost-effective resource for patient recruitment in clinical research. However, how to optimally select a cohort fr…
Variable selection with multiply-imputed datasets: choosing between stacked and grouped methods
Jiacong Du, Jonathan Boss, Peisong Han +5
Penalized regression methods, such as lasso and elastic net, are used in many biomedical applications when simultaneous regression coefficient estimation and variable selection is…
A stacked approach for chained equations multiple imputation incorporating the substantive model
Lauren Beesley, Jeremy M G Taylor
Multiple imputation by chained equations (MICE) has emerged as a popular approach for handling missing data. A central challenge for applying MICE is determining how to incorporate…