Results 71 to 80 of about 566,893 (298)

Data‐Driven SuStaIn Model of Disability Progression in Amyotrophic Lateral Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
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, Veria Vacchiano, Vittorio Velucci, Stefano Zoccolella, Rocco Liguori, Giovanni Defazio   +5 more
wiley   +1 more source

Multiple Comparisons for a Psychophysical Test in Bootstrap Logistic Regression

Journal of Algorithms & Computational Technology, 2014
We propose an algorithm of multiple comparisons with a control for a psychophysical test. Our algorithm is based on the step-down procedure and is applicable to the bootstrap test in logistic regression.
Norihiro Mita, Hiroshi Sasaki, Kazutaka Kani, Akio Tabuchi, Heihachiro Hara   +4 more
doaj   +1 more source

Early Clinical and Cerebrospinal Fluid Predictors of 1‐Year Recurrence in Autoimmune GFAP Astrocytopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong, Yuping Xiao, Yuhan Wu, Ziyuan Huang, Weishan Liang, Li Xiao, Yaqing Shu, Tingting Lu, Yanyu Chang, Wei Qiu, Yuge Wang   +10 more
wiley   +1 more source

ESTIMACIÓN DE KAPLAN MEIER BOOTSTRAP DE LA CURVA DE SUPERVIVENCIA

Pesquimat, 2014
In this work the function of survival is estimated by means of the non-parametric method known like the Kaplan Meier Bootstrap estimator, under the assumption of asymptotical normality.
Freddy Tineo Guevara, Ysela Dominga Agüero Palacios, Emma Norma Cambillo Moyano   +2 more
doaj   +1 more source

Biopsychosocial Determinants of Hand Function and Its Trajectories Over Five Years in Patients With Hand Osteoarthritis

Arthritis Care &Research, EarlyView.
Objective This study aimed to investigate hand function trajectories over five years in primary hand osteoarthritis (OA). Additionally, determinants of baseline and longitudinal hand function were assessed. Methods A total of 538 patients with both baseline and five‐year study visits were analyzed.
Annemiek V. E. M. Olde Meule, Coen van der Meulen, Jos Runhaar, Frits R. Rosendaal, Margreet Kloppenburg   +4 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
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, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

A Non-Parametric Bootstrap for Spectral Clustering

, 2022
Finite mixture modelling is a popular method in the field of clustering and is beneficial largely due to its soft cluster membership probabilities. A common method for fitting finite mixture models is to employ spectral clustering, which can utilize the expectation-maximization (EM) algorithm.
Welsh, Liam, Shreeves, Phillip
openaire   +2 more sources

Machine Learning Hazard Estimation with Valid Bootstrap Inference for Generalized Progressive Hybrid Censoring

Mathematics
Reliability studies frequently employ progressive censoring schemes that remove surviving units during testing, yet statistical inference under such designs remains vulnerable to parametric model misspecification.
Sherif I. Ammar, Faizah T. Alamri, Faiza A. Althubyani, Mahmoud H. Abu-Moussa   +3 more
doaj   +1 more source

On the Simulation Study of Jackknife and Bootstrap MSE Estimators of a Domain Mean Predictor for Fay‑Herriot Model

Acta Universitatis Lodziensis. Folia Oeconomica, 2017
We consider the problem of the estimation of the mean squared error (MSE) of some domain mean predictor for Fay‑Herriot model. In the simulation study we analyze properties of eight MSE estimators including estimators based on the jackknife method (Jiang,
Małgorzata Karolina Krzciuk
doaj   +1 more source