Meta-analysis of individualized treatment rules via sign-coherency

1 code implementation • 28 Nov 2022 • Jay Jojo Cheng, Jared D. Huling, Guanhua Chen

Medical treatments tailored to a patient's baseline characteristics hold the potential of improving patient outcomes while reducing negative side effects.

A method for comparing multiple imputation techniques: a case study on the U.S. National COVID Cohort Collaborative

no code implementations • 13 Jun 2022 • Elena Casiraghi, Rachel Wong, Margaret Hall, Ben Coleman, Marco Notaro, Michael D. Evans, Jena S. Tronieri, Hannah Blau, Bryan Laraway, Tiffany J. Callahan, Lauren E. Chan, Carolyn T. Bramante, John B. Buse, Richard A. Moffitt, Til Sturmer, Steven G. Johnson, Yu Raymond Shao, Justin Reese, Peter N. Robinson, Alberto Paccanaro, Giorgio Valentini, Jared D. Huling, Kenneth Wilkins, :, Tell Bennet, Christopher Chute, Peter DeWitt, Kenneth Gersing, Andrew Girvin, Melissa Haendel, Jeremy Harper, Janos Hajagos, Stephanie Hong, Emily Pfaff, Jane Reusch, Corneliu Antoniescu, Kimberly Robaski

In this paper, we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques.

Imputation

Robust Sample Weighting to Facilitate Individualized Treatment Rule Learning for a Target Population

no code implementations • 3 May 2021 • Rui Chen, Jared D. Huling, Guanhua Chen, Menggang Yu

The aim of this paper is to develop a weighting framework to mitigate the impact of such misspecification and thus facilitate the generalizability of optimal ITRs from a source population to a target population.

Fast Penalized Regression and Cross Validation for Tall Data with the oem Package

2 code implementations • 29 Jan 2018 • Jared D. Huling, Peter Z. G. Qian

A large body of research has focused on theory and computation for variable selection techniques for high dimensional data.

Computation