Multiply robust generalized estimating equations for cluster randomized trials with missing outcomes. [PDF]
Rabideau DJ, Li F, Wang R.
europepmc +1 more source
Generalized Equations for Estimating DXA Percent Fat of Diverse Young Women and Men
Daniel P. O’Connor +5 more
openalex +2 more sources
A rationally engineered bifunctional photocatalyst is reported, which achieves simultaneous selective oxidation of biomass‐derived 5‐hydroxymethylfurfural (HMF) to 2,5‐diformylfuran (DFF) and efficient H2 evolution. By precisely positioning Au and Co3O4 on Zn3In2S6 nanosheet, dual interfacial electric fields are well constructed to spatially separate ...
Shiqing Li +8 more
wiley +1 more source
Optimal designs using generalized estimating equations in cluster randomized crossover and stepped wedge trials. [PDF]
Liu J, Li F.
europepmc +1 more source
Application of generalized estimating equation (GEE) model on students' academic performance
Isaac Owusu-Darko +2 more
openalex +1 more source
Design and Applications of Multi‐Frequency Programmable Metamaterials for Adaptive Stealth
This article provides a comprehensive overview of metamaterials, including their fundamental principles, properties, synthesis techniques, and applications in stealth, as well as their challenges and future prospects. It covers topics that are more advanced than those typically discussed in existing review articles, while still being closely connected ...
Jonathan Tersur Orasugh +4 more
wiley +1 more source
Designing individually randomized group treatment trials with repeated outcome measurements using generalized estimating equations. [PDF]
Wang X, Turner EL, Li F.
europepmc +1 more source
Generalized kernel estimating equation for panel estimation of small area unemployment rates [PDF]
Jooyong Shim +2 more
openalex +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source

