Results 81 to 90 of about 15,712,923 (297)

Longitudinal Changes in Adiposity After a Youth Sport‐Related Knee Injury: Informing Posttraumatic Osteoarthritis Prevention

Arthritis Care &Research, EarlyView.
Objective Youth who experience a sport‐related knee injury have elevated odds of becoming overweight or developing obesity in 3 to 10 years, compounding their risk for posttraumatic osteoarthritis (PTOA). To inform prevention strategies, this study compared patterns of adiposity change between youth with a sport‐related knee injury and uninjured youth ...
Justin M. Losciale, Nuria E. J. Jansen, Christina Y. Le, Leo Lu, Hui Xie, Marienke van Middelkoop, Jackie L. Whittaker   +6 more
wiley   +1 more source

Bayesian Panel Variable Selection Under Model Uncertainty for High-Dimensional Data

Econometrics
Selecting the relevant covariates in high-dimensional panel data remains a central challenge in applied econometrics. Conventional fixed effects and random effects models are not designed for systematic variable selection under model uncertainty.
Pathairat Pastpipatkul, Htwe Ko
doaj   +1 more source

Real‐World Effectiveness and Safety of Secukinumab in Giant Cell Arteritis: An Italian Multicenter Cohort Study

Arthritis Care &Research, EarlyView.
Objective The objective of this study was to evaluate the real‐world effectiveness and safety of secukinumab in patients with giant cell arteritis (GCA). Methods This multicenter retrospective study included patients with GCA who received secukinumab at 14 Italian centers with at least six months of follow‐up.
Luca Iorio, Federica Davanzo, Caterina Ricordi, Milena Bond, Ruggiero Mascolo, Jacopo Mora, Alessandro Tomelleri, Angelo Fassio, Francesca Cuzzocrea, Sara Monti, Edoardo Conticini, Fabiola Atzeni, Paolo Delvino, Carlotta Nannini, Augusta Ortolan, Francesco Pollastri, Ester Vivaldelli, Chiara Marvisi, Paola Toniati, Antonio Brucato, Alessandra Milanesi, Francesca Regola, Enrico Tombetti, Lorenzo Dagna, Roberta Ramonda, Christian Dejaco, Luca Quartuccio, Carlo Salvarani, Roberto Padoan   +28 more
wiley   +1 more source

Bayesian variable selection for genome-wide association study of grain traits in rice.

PLoS ONE
Rice (Oryza sativa) is a staple food crop for more than half of the world's population. Besides high gluten-free nutritional contents, it has high economic value supporting livelihood of millions of farmers. That is why a lot of research is being carried
Rupam Basu, Sabyasachi Mukhopadhyay, Kaustubh Adhikari   +2 more
doaj   +1 more source

Statistical inference for nonignorable missing-data problems: a selective review

Statistical Theory and Related Fields, 2018
Nonignorable missing data are frequently encountered in various settings, such as economics, sociology and biomedicine. We review statistical inference for nonignorable missing-data problems, including estimation, influence analysis and model selection ...
Niansheng Tang, Yuanyuan Ju
doaj   +1 more source

The association of gout flare resolution with physical activity and sleep: a prospective remote‐monitoring study

Arthritis Care &Research, Accepted Article.
Objectives This study aimed to determine whether gout flare resolution is associated with physical activity and sleep. These findings were intended to inform the future development of a definition for flare resolution. Methods Data from 81 participants with gout who experienced >1 flare during a 6‐month prospective observational study were included ...
Sarah Stewart, Boston Girven, Mia Clarke, Irene Zeng, Angelo Gaffo, Lisa K Stamp, N Lawrence Edwards, David Rice, Tania Ka'ai, Karl Rudolph, Julie Collis, Nicola Kayes, Nicola Dalbeth   +12 more
wiley   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Minimum uncertainty as Bayesian network model selection principle

BMC Bioinformatics
Background Bayesian Network (BN) modeling is a prominent methodology in computational systems biology. However, the incommensurability of datasets frequently encountered in life science domains gives rise to contextual dependence and numerical ...
Grigoriy Gogoshin, Andrei S. Rodin
doaj   +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

Bayesian Model Selection of Regular Vine Copulas

, 2018
Regular vine copulas are a flexible class of dependence models, but Bayesian methodology for model selection and inference is not yet fully developed.
Gruber, L. and Czado, D.
core   +1 more source