Robust Henderson III Estimators of Variance Components in the Nested Error Model [PDF]
Common methods for estimating variance components in Linear Mixed Models include Maximum Likelihood (ML) and Restricted Maximum Likelihood (REML). These methods are based on the strong assumption of multivariate normal distribution and it is well know that they are very sensitive to outlying observations with respect to any of the random components ...
Molina, Isabel +2 more
openaire +3 more sources
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
An Experimentally Parameterized Equivalent Circuit Model of a Solid-State Lithium-Sulfur Battery
This paper presents and parameterizes an equivalent circuit model of an all-solid-state lithium-sulfur battery cell, filling a gap in the literature associated with low computational intensity models suitable for embedded battery management applications.
Timothy Cleary +5 more
doaj +1 more source
A nested error regression model with high-dimensional parameter for small area estimation
Abstract In this paper, we propose a flexible nested error regression small area model with high-dimensional parameter that incorporates heterogeneity in regression coefficients and variance components. We develop a new robust small area-specific estimating equations method that allows appropriate pooling of a large number of areas in ...
Lahiri, Partha, Salvati, Nicola
openaire +3 more sources
Global Rather Than Vertical‐Selective Saccadic Abnormalities in Progressive Supranuclear Palsy
ABSTRACT Objective To test whether vertical saccades are preferentially affected in Progressive Supranuclear Palsy (PSP). Methods PSP patients (n = 24) were compared to age‐matched controls (n = 94) and two degenerative groups (Alzheimer's disease, n = 20; Lewy body disease, n = 50).
Duy Duan Nguyen +6 more
wiley +1 more source
Arterial Spin‐Labeling MRI at the Cortical‐CSF Interface: A Novel Biomarker in Alzheimer Disease
ABSTRACT Background/Objective Arterial spin‐labeling (ASL) MRI can measure perfusion signal adjacent to CSF spaces and may provide information regarding CSF‐adjacent water transport physiology. We developed an automated pipeline to extract cortical‐CSF interface (IF) perfusion for comparison between Alzheimer disease (AD) and cognitively normal ...
Mona Asghariahmadabad +22 more
wiley +1 more source
Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis
ABSTRACT Objective To determine whether ordinal Subtype and Stage Inference (SuStaIn) applied to routine ALSFRS‐R item scores can identify reproducible disability progression patterns in amyotrophic lateral sclerosis (ALS) and provide clinically meaningful staging.
Giammarco Milella +5 more
wiley +1 more source
Automating nested watershed delineation over the world considering endorheic basins and islands
Global-scale nested watershed datasets are foundational for hydrological studies. However, their construction is not yet fully automated, making the process labor-intensive and time-consuming, primarily due to the lack of algorithms capable of encoding ...
Junzhi Liu +5 more
doaj +1 more source
The Power of F Tests Under Regression Models with Nested Error Structure
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Rao, J.N.K., Wang, S.G.
openaire +2 more sources
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source

