Results 171 to 180 of about 10,813 (266)
Improved risk prediction via cross-domain calibration in a retrospective case-control study. [PDF]
Zhao G, Ma Y, Cao Y.
europepmc +1 more source
LLM‐based prior elicitation for Bayesian graphical modeling
ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski +2 more
wiley +1 more source
To vary or not to vary: A flexible empirical Bayes factor for testing variance components
Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley +1 more source
Regularized reduced rank regression for mixed predictor and response variables
Abstract In this paper, we introduce the Generalized Mixed Regularized Reduced Rank Regression model (GMR4), an extension of the GMR3 model designed to improve performance in high‐dimensional settings. GMR3 is a regression method for a mix of numeric, binary and ordinal response variables, while also allowing for mixed‐type predictors through optimal ...
Lorenza Cotugno +2 more
wiley +1 more source
A review of aeroelastic instabilities and resonance effects in wind turbine blade dynamics. [PDF]
Saram MU, Yang J.
europepmc +1 more source
Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source
Jacobian Granger causality for count and binary data with applications to causal network inference. [PDF]
Suryadi, Chew LY, Ong YS.
europepmc +1 more source
Multidimensional unipolar IRT and applications to the measurement of print exposure
Abstract Item response theory (IRT) has been a prominent modelling framework in educational and psychological measurement. Traditional IRT models are bipolar, commonly assuming symmetric measurement link functions and symmetric trait distributions over a latent continuum unbounded at both ends. However, many measured constructs, such as print exposure,
Qi (Helen) Huang, Daniel M. Bolt
wiley +1 more source

