Results 1 to 10 of about 1,125,399 (157)
Fixed or random? On the reliability of mixed‐effects models for a small number of levels in grouping variables [PDF]
Ecology and Evolution, 2022 Biological data are often intrinsically hierarchical (e.g., species from different genera, plants within different mountain regions), which made mixed‐effects models a common analysis tool in ecology and evolution because they can account for the non ...
Johannes Oberpriller +2 more
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Understanding Mixed-Effects Models Through Data Simulation
Advances in Methods and Practices in Psychological Science, 2021 Experimental designs that sample both subjects and stimuli from a larger population need to account for random effects of both subjects and stimuli using mixed-effects models.
Lisa M. DeBruine, Dale J. Barr
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Model Specification in Mixed-Effects Models
Communications in Kinesiology, 2023 Mixed-effect models are flexible tools for researchers in a myriad of fields, but that flexibility comes at the cost of complexity and if users are not careful in how their model is specified, they could be making faulty inferences from their data.
Keith Lohse +2 more
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Coefficients of Determination for Mixed-Effects Models. [PDF]
J Agric Biol Environ Stat, 2022 The coefficient of determination is well defined for linear models and its extension is long wanted for mixed-effects models. We revisit its extension to define measures for proportions of variation explained by the whole model, fixed effects only, and random effects only.
Zhang D.
europepmc +3 more sources
Fiducial Inference in Linear Mixed-Effects Models [PDF]
EntropyWe develop a novel framework for fiducial inference in linear mixed-effects (LME) models, with the standard deviation of random effects reformulated as coefficients.
Jie Yang +3 more
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Mixed‐effects models and the drug titration paradox [PDF]
CPT: Pharmacometrics & Systems Pharmacology, 2023 Charles F. Minto, Thomas W. Schnider
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Mixed effects regression models in forestry research [PDF]
Сибирский лесной журнал, 2021 A promising method for finding patterns in experimental data is regression models of mixed effects, which have not found wide application in forest science in Russia to date.
A. V. Lebedev, V. V. Kuzmichev
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Mixed-effect models with trees
Advances in Data Analysis and Classification, 2022 AbstractTree-based regression models are a class of statistical models for predicting continuous response variables when the shape of the regression function is unknown. They naturally take into account both non-linearities and interactions. However, they struggle with linear and quasi-linear effects and assume iid data.
Anna Gottard +3 more
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Decentralized Mixed Effects Modeling in COINSTAC
Neuroinformatics, 2023 Abstract Performing group analysis on magnetic resonance imaging (MRI) data with linear mixed-effects (LME) models is challenging due to its large dimensionality and inherent multi-level covariance structure. In addition, as large-scale collaborative projects become commonplace in neuroimaging, data must increasingly ...
Sunitha Basodi +7 more
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Invited review: Recursive models in animal breeding: Interpretation, limitations, and extensions
Journal of Dairy Science, 2023 : Structural equation models allow causal effects between 2 or more variables to be considered and can postulate unidirectional (recursive models; RM) or bidirectional (simultaneous models) causality between variables.
L. Varona, O. González-Recio
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