Results 31 to 40 of about 18,910,981 (254)
Linear mixed models for series of variety trials [PDF]
, 2011 When using linear mixed models for analysis of series of variety trials, the statistical inference space is dependent on the design of the series. In this paper, four inference spaces are recognized for one-year crop variety trials: single-year local ...
Forkman, Johannes
core +1 more source
Environment International, 2022 Background: The impacts of long-term high exposure to PM2.5 in workplace on glucose metabolism in asymptomatic working adults (AWAs) have rarely been explored.
Jiangshan He +15 more
doaj +1 more source
Diversity and complexity in neural organoids
FEBS Letters, EarlyView.Neural organoid research aims to expand genetic diversity on one side and increase tissue complexity on the other. Chimeroids integrate multiple donor genomes within single organoids. Self‐organising multi‐identity organoids, exogenous cell seeding, or enforced assembly of region‐specific organoids contribute to tissue complexity.
Ilaria Chiaradia, Madeline A. Lancaster
wiley +1 more source
Revstat Statistical Journal, 2018 The generalized linear mixed effects model (GLMM) approach is widely used to analyze longitudinal binary data when the goal of the study is a subject-specific interpretation because it allows missing values on the response, provided they are missing at ...
M. Salomé Cabral +1 more
doaj +1 more source
The human gut microbiome across the life course
FEBS Letters, EarlyView.Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero +4 more
wiley +1 more source
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
A variance shilf model for outlier detection and estimation in linear and linear mixed models [PDF]
, 2008 Includes abstract.Includes bibliographical references.Outliers are data observations that fall outside the usual conditional ranges of the response data.They are common in experimental research data, for example, due to transcription errors or faulty ...
Gumedze, Freedom Nkhululeko
core +1 more source
Mixed effect models in distance sampling [PDF]
, 2013 Recently, much effort has been expended for improving conventional distance sampling methods, e.g. by replacing the design-based approach with a model-based approach where observed counts are related to environmental covariates (Hedley and Buckland, 2004)
Oedekoven, Cornelia Sabrina
core +2 more sources
MathematicsEnhancing model interpretability remains an ongoing challenge in predictive modelling, especially when applied to simulation data from complex systems.
Shengkun Xie +2 more
doaj +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source