Results 201 to 210 of about 6,450 (280)

Variable Selection for Illness‐Death Processes Under Dual Observation Schemes

Statistics in Medicine, Volume 45, Issue 13-14, June 2026.
ABSTRACT The classical illness‐death process offers a useful framework for studying the progression of chronic disease while jointly modeling death. In many settings the time of disease progression is not observed directly, but progression status is recorded at intermittent assessment times.
Xianwei Li, Liqun Diao, Richard J. Cook
wiley   +1 more source

A Functional Joint Model for Survival and Multivariate Sparse Functional Data in Multi-Cohort Alzheimer's Disease Study. [PDF]

Stat Med
Wang W, Xiao L, Li R, Luo S, Alzheimer's Disease Neuroimaging Initiative.   +4 more
europepmc   +1 more source

Empirical Comparison of Win Ratio and Joint Frailty Models for Recurrent Event Endpoints With Applications in Oncology and Cardiology

Statistics in Medicine, Volume 45, Issue 13-14, June 2026.
ABSTRACT Composite endpoints that combine recurrent non‐fatal events with a terminal event are increasingly used in randomized clinical trials, yet conventional time‐to‐first event analyses may obscure clinically relevant information. We compared two statistical frameworks tailored to such endpoints: the joint frailty model (JFM) and the last‐event ...
Adrien Orué, Derek Dinart, Laurent Billot, Carine Bellera, Virginie Rondeau   +4 more
wiley   +1 more source

Marbling Matters: Lean and Fatty Red Meat Show Opposing Associations with Brain Structural Indices. [PDF]

Nutrients
Klinedinst BS, Dawson AL, DelCasale M, Venkateswaran A, Willette AA.   +4 more
europepmc   +1 more source

Missing comparability: When genomic selection faces field variability. A case study in soybeans

The Plant Genome, Volume 19, Issue 2, June 2026.
Abstract The processing of phenotypic information prior to training genomic selection (GS) models is a key factor that is frequently overlooked. Several approaches have been proposed to isolate the genetic signal from the field variability. However, in most cases, the estimated genetic signal still carries the field variability print.
Edmundo Caballero, Julian Garcia‐Abadillo, Diego Jarquin   +2 more
wiley   +1 more source

Bayesian probabilistic projections of proportions with limited data: An application to subnational contraceptive method supply shares. [PDF]

PLoS One
Comiskey H, Cahill N, Alkema L, Frazier DT, Maneesoonthorn W.   +4 more
europepmc   +1 more source

An Overview of Artificial Intelligence and Machine Learning Approaches for Building Energy Analysis, Characterization, Control, and Grid Support Services Provision

WIREs Energy and Environment, Volume 15, Issue 2, June 2026.
Artificial Intelligence and Machine Learning Approaches used in Building Energy Analysis, Control, and Provision of Grid Support Services. ABSTRACT Increasing penetrations of variable renewable energy sources like wind and solar photovoltaic (PV) systems are challenging power system stability worldwide.
Jack S. Bryant, Hangxin Li, Nawanjana Maheepala, Xiaoyu Lin, Mingkun Dai, Binglong Han, Robin Guan, Lasantha Meegahapola, Shengwei Wang, Dilan Robert, Liuping Wang, Fu Xiao   +11 more
wiley   +1 more source

Morphological indicators of puberty in 3/4 and 5/8 Girolando heifers. [PDF]

Trop Anim Health Prod
Böck MJ, Schimidt APP, Penitente-Filho JM, Dos Santos MG, Rocha RFB, Guimarães JD, Guimarães SEF.   +6 more
europepmc   +1 more source

On the Foundational Arguments of Sufficient Dimension Reduction

WIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Physical Activity in Osteosarcoma Patients During and Post Therapy: A Single Site Prospective Observational Study. [PDF]

Cancer Med
Cohen ER, Andersen C, Moody K, Swartz MC, Robertson MC, Rajan A, Honey T, Lugo S, Waterman G, Schadler K.   +9 more
europepmc   +1 more source