Results 121 to 130 of about 1,128,323 (301)

Uncertainty under a multivariate nested-error regression model with logarithmic transformation [PDF]

, 2006
Assuming a multivariate linear regression model with one random factor, we consider the parameters defined as exponentials of mixed effects, i.e., linear combinations of fixed and random effects.
Molina, Isabel
core   +1 more source

Discovery and Targeted Proteomic Studies Reveal Striatal Markers Validated for Huntington's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Clinical trials for Huntington's disease (HD) enrolling persons before clinical motor diagnosis (CMD) lack validated biomarkers. This study aimed to conduct an unbiased discovery analysis and a targeted examination of proteomic biomarkers scrutinized by clinical validation. Methods Cerebrospinal fluid was obtained from PREDICT‐HD and
Daniel Chelsky, Cara Joyce, H. Jeremy Bockholt, Paul A. Rudnick, William H. Adams, Fiona McAllister, Justin W. Smock, Michael A. Newton, Jane S. Paulsen   +8 more
wiley   +1 more source

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Heteroskedasticity-robust inference in linear regression models

Journal of the American Statistical Association (in press), 2018
This paper considers inference in heteroskedastic linear regression models with many control variables. The slope coefficients on these variables are nuisance parameters. Our setting allows their number to grow with the sample size, possibly at the same rate, in which case they are not consistently estimable.
openaire   +2 more sources

Scalable Bayesian Inference on High-Dimensional Multivariate Linear Regression

Bayesian Analysis
We consider jointly estimating the coefficient matrix and the error precision matrix in high-dimensional multivariate linear regression models. Bayesian methods in this context often face computational challenges, leading to previous approaches that either utilize a generalized likelihood without ensuring the positive definiteness of the precision ...
Cao, Xuan, Lee, Kyoungjae
openaire   +2 more sources

Prognostic Implications of Sleep Architecture for Patients Admitted to the Intensive Care Unit With Status Epilepticus

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Status epilepticus (SE) is associated with significant mortality. Sleep architecture may reflect normal brain function. Impaired sleep architecture is associated with poorer outcomes in numerous conditions. Here we investigate the association of sleep architecture in continuous EEG (cEEG) with survival in SE.
Ran R. Liu, Marcus C. Ng, Gavin P. Winston, Sabrina Schaly, Garima Shukla, Lysa Boissé Lomax   +5 more
wiley   +1 more source

Predicting Standardized Streamflow index for hydrological drought using machine learning models

Engineering Applications of Computational Fluid Mechanics, 2020
Hydrological droughts are characterized based on their duration, severity, and magnitude. Among the most critical factors, precipitation, evapotranspiration, and runoff  are essential in modeling the droughts. In this study, three indices of drought, i.e.
Shahabbodin Shamshirband, Sajjad Hashemi, Hana Salimi, Saeed Samadianfard, Esmaeil Asadi, Sadra Shadkani, Katayoun Kargar, Amir Mosavi, Narjes Nabipour, Kwok-Wing Chau   +9 more
doaj   +1 more source

Structured Learning via Logistic Regression [PDF]

, 2014
A successful approach to structured learning is to write the learning objective as a joint function of linear parameters and inference messages, and iterate between updates to each.
Domke, Justin
core  

Cognitive Status in People With Epilepsy in the Republic of Guinea: A Prospective, Case–Control Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective People with epilepsy (PWE) may experience cognitive deficits but fail to undergo formal evaluation. This study compares cognitive status between PWE and healthy controls in the West African Republic of Guinea. Methods A cross‐sectional, case–control study was conducted in sequential recruitment phases (July 2024–July 2025) at Ignace ...
Maya L. Mastick, Cheick O. Soumah, Malé Doré, Oumar Mara, Desiré Neldje, Fodé A. Cissé, Toure M. Lamine, Aminata Diallo, Seungwon Lee, Siddharth Satish, Alexander J. X. Chen, Alice Liu, Nomin Enkhtsetseg, Farrah J. Mateen, The Guinea Epilepsy Project   +14 more
wiley   +1 more source

On decompositions of estimators under a general linear model with partial parameter restrictions

Open Mathematics, 2017
A general linear model can be given in certain multiple partitioned forms, and there exist submodels associated with the given full model. In this situation, we can make statistical inferences from the full model and submodels, respectively.
Jiang Bo, Tian Yongge, Zhang Xuan
doaj   +1 more source