Results 171 to 180 of about 290,361 (291)

Regulatory Experiences with the Use of Multiple Imputation for Missing Data in a Phase 3 Confirmatory Trial. [PDF]

Ther Innov Regul Sci
Sassi-Sayadi M, Verweij P, Cornelisse P.
europepmc   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Multiple imputation for missing values in ordinal variables from cancer registry data when performing Cox proportional hazards regression. [PDF]

BMC Med Res Methodol
Kästner A, Hoffmann W, Hüsing J, Stang A, Hüsing A.   +4 more
europepmc   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

A New Multiple Imputation Method for High-Dimensional Neuroimaging Data. [PDF]

Hum Brain Mapp
Lu T, Kochunov P, Chen C, Huang HH, Hong LE, Chen S.   +5 more
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

Two-stage multiple imputation with a longitudinal composite variable. [PDF]

BMC Med Res Methodol
Wang X, Larson MG, Liu C.
europepmc   +1 more source

Food inflation pass‐through from agricultural imports in a small open economy

American Journal of Agricultural Economics, EarlyView.
Abstract This paper develops a new framework for quantifying cost pass‐through in a small open economy by estimating firm‐level markup responses to agricultural import price shocks. We show theoretically that markup adjustments depend on firms' reliance on imported inputs and demand curvature, generating heterogeneous inflationary effects across firm ...
Minseong Kang, Seungki Lee
wiley   +1 more source

Reference-Based Multiple Imputation for Longitudinal Binary Data. [PDF]

Stat Med
Cro S, Quartagno M, White IR, Carpenter JR.   +3 more
europepmc   +1 more source

Multiple Imputation Technique [PDF]

, 2020
openaire   +1 more source