Results 71 to 80 of about 4,151,630 (320)
, 2013 The effects of different parametrizations on the convergence of Bayesian computational algorithms for hierarchical models are well explored. Techniques such as centering, noncentering and partial noncentering can be used to accelerate convergence in MCMC
Nott, David J., Tan, Linda S. L.
core +1 more source
Best practice guidance for linear mixed-effects models in psychological science
Journal of Memory and Language, 2019 The use of Linear Mixed Effects Models (LMMs) is set to dominate statistical analyses in psychological science and may become the default approach to analyzing quantitative data. The rapid growth in adoption of LMMs has been matched by a proliferation of
L. Meteyard, Robert A. I. Davies
semanticscholar +1 more source
Bayesian Boosting for Linear Mixed Models
CoRR, 2021 Boosting methods are widely used in statistical learning to deal with high-dimensional data due to their variable selection feature. However, those methods lack straightforward ways to construct estimators for the precision of the parameters such as variance or confidence interval, which can be achieved by conventional statistical methods like Bayesian
Boyao Zhang +4 more
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Children with acute lymphoblastic leukemia (ALL) are at risk of severe outcomes from SARS‐CoV‐2 (SCV2). In the post‐pandemic context, where most children have been infected with SCV2, there are limited data on whether vaccination remains beneficial in children with ALL.
Janna R. Shapiro +11 more
wiley +1 more source
Mean squared error of empirical predictor
, 2004 The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are ...
Das, Kalyan +2 more
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Mapping the evolution of mitochondrial complex I through structural variation
FEBS Letters, EarlyView.Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin +2 more
wiley +1 more source
Prediction of genetic value in F3 populations of Avena sativa L. using Reml/Blup
Crop Breeding and Applied Biotechnology, 2005 In genetics and breeding studies it is common to conduct experiments of fixed (sowing method) and random (populations) factors. Therefore, the most appropriate statistic analyses would use mixed linear models.
Jefferson Luís Meirelles Coimbra +6 more
doaj
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
wiley +1 more source
Improved testing inference in mixed linear models
, 2009 Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit.
Barndorff-Nielsen +23 more
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