Results 81 to 90 of about 539,449 (277)

Addressing Economic Insecurities Can Improve Patient‐Reported Outcomes in Lupus

Arthritis Care &Research, Accepted Article.
Background Economic insecurities, such as food, housing, transportation, and financial challenges, are modifiable risk factors and influence patient‐reported outcomes (PROs) in systemic lupus erythematosus (SLE). We examined: 1) associations between economic insecurities and PROs; 2) the impact of screening and addressing economic insecurities during ...
Jay Patel, Tripti Singh, Meredith Ingersoll, Shelby Gomez, Amanda Weber, Sarah E. Panzer, Sancia Ferguson, Christie M. Bartels, Shivani Garg   +8 more
wiley   +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

Information use by humans during dynamic route choice in virtual crowd evacuations [PDF]

Royal Society Open Science, 2015
We conducted a computer-based experiment with over 450 human participants and used a Bayesian model selection approach to explore dynamic exit route choice mechanisms of individuals in simulated crowd evacuations.
Nikolai W. F. Bode, Armel U. Kemloh Wagoum, Edward A. Codling   +2 more
doaj   +1 more source

The role of Bayesian philosophy within Bayesian model selection [PDF]

European Journal for Philosophy of Science, 2012
AbstractBayesian model selection has frequently been the focus of philosophical inquiry (e.g., Forster, Br J Philos Sci 46:399–424, 1995; Bandyopadhyay and Boik, Philos Sci 66:S390–S402, 1999; Dowe et al., Br J Philos Sci 58:709–754, 2007). This paper argues that Bayesian model selection procedures are very diverse in their inferential target and their
openaire   +4 more sources

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

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

Comment on `Tainted evidence: cosmological model selection versus fitting', by Eric V. Linder and Ramon Miquel (astro-ph/0702542v2) [PDF]

, 2007
In astro-ph/0702542v2, Linder and Miquel seek to criticize the use of Bayesian model selection for data analysis and for survey forecasting and design.
Corasaniti, Pier Stefano, Kunz, Martin, Liddle, Andrew R, Mukherjee, Pia, Parkinson, David, Trotta, Roberto   +5 more
core   +2 more sources

Considerate Approaches to Achieving Sufficiency for ABC model selection

, 2011
For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to problems where we can use simulations from a model ...
Chris Barnes, Michael Stumpf, Michael Stumpf, Sarah Filippi, Tom Thorne   +4 more
core   +1 more source

Efficient Bayesian Regularization for Graphical Model Selection

Bayesian Analysis, 2019
There has been an intense development in the Bayesian graphical model literature over the past decade; however, most of the existing methods are restricted to moderate dimensions. We propose a novel graphical model selection approach for large dimensional settings where the dimension increases with the sample size, by decoupling model fitting and ...
Kundu, Suprateek, Mallick, Bani K., Baladandayuthapani, Veera   +2 more
openaire   +4 more sources

Integrative Approaches for DNA Sequence‐Controlled Functional Materials

Advanced Functional Materials, EarlyView.
DNA is emerging as a programmable building block for functional materials with applications in biomimicry, biochemical, and mechanical information processing. The integration of simulations, experiments, and machine learning is explored as a means to bridge DNA sequences with macroscopic material properties, highlighting current advances and providing ...
Aaron Gadzekpo, Ewa Anna Oprzeska‐Zingrebe, Mariana Kozlowska, Lennart Hilbert, Iliya D. Stoev   +4 more
wiley   +1 more source