Results 61 to 70 of about 658,808 (305)
Quasi-Monte Carlo EM algorithm for MLEs in generalized linear mixed models
, 1998 Inferences for generalized linear mixed models are greatly hampered by the intractable integrated likelihood. In this paper numerical integration based on Quasi-Monte Carlo method is used to approximate the integral of the EM algorithm and then to fit ...
Robin Thompson +3 more
core +1 more source
Modeling Multiple Item Context Effects With Generalized Linear Mixed Models
Frontiers in Psychology, 2019 Item context effects refer to the impact of features of a test on an examinee's item responses. These effects cannot be explained by the abilities measured by the test. Investigations typically focus on only a single type of item context effects, such as
Norman Rose +6 more
doaj +1 more source
FEBS Letters, EarlyView.We reconstituted Synechocystis glycogen synthesis in vitro from purified enzymes and showed that two GlgA isoenzymes produce glycogen with different architectures: GlgA1 yields denser, highly branched glycogen, whereas GlgA2 synthesizes longer, less‐branched chains.
Kenric Lee +3 more
wiley +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
Prediction in linear mixed models
, 2004 Following estimation of effects from a linear mixed model, it is often useful to form predicted values for certain factor/variate combinations. The process has been well defined for linear models, but the introduction of random effects into the model ...
Gogel, Beverley +9 more
core +1 more source
Spatial Autoregressive Modeling on Linear Mixed Models for Dependency Between Regions
Aceh International Journal of Science and Technology, 2023 This study develops a linear mixed model (LMM) that includes spatial effects between regions with a spatial autoregressive model (SAR model). Between observations (regions) on that LMM are usually assumed to be independent. However, these assumptions are
Timbang Sirait
doaj +1 more source
FEBS Letters, EarlyView.We identified a systemic, progressive loss of protein S‐glutathionylation—detected by nonreducing western blotting—alongside dysregulation of glutathione‐cycle enzymes in both neuronal and peripheral tissues of Taiwanese SMA mice. These alterations were partially rescued by SMN antisense oligonucleotide therapy, revealing persistent redox imbalance as ...
Sofia Vrettou, Brunhilde Wirth
wiley +1 more source
FEBS Letters, EarlyView.In this study, we found that human cervical‐derived adipocytes maintain intracellular iron level by regulating the expression of iron transport‐related proteins during adrenergic stimulation. Melanotransferrin is predicted to interact with transferrin receptor 1 based on in silico analysis.
Rahaf Alrifai +9 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
On non-negative estimation of variance components in mixed linear models
Journal of Advanced Research, 2016 Alternative estimators have been derived for estimating the variance components according to Iterative Almost Unbiased Estimation (IAUE). As a result two modified IAUEs are introduced.
Heba A. El Leithy +2 more
doaj +1 more source