Results 21 to 30 of about 819,272 (292)

LINEAR, GENERALIZED, HIERARCHICAL, BAYESIAN AND RANDOM REGRESSION MIXED MODELS IN GENETICS/GENOMICS IN PLANT BREEDING

open access: yesFunctional Plant Breeding Journal, 2020
This paper presents the state of the art of the statistical modelling as applied to plant breeding. Classes of inference, statistical models, estimation methods and model selection are emphasized in a practical way.
Marcos Deon Vilela de Resende   +1 more
semanticscholar   +1 more source

Estimation Curve of Mixed Spline Truncated and Fourier Series Estimator for Geographically Weighted Nonparametric Regression

open access: yesMathematics, 2022
Geographically Weighted Regression (GWR) is the development of multiple linear regression models used in spatial data. The assumption of spatial heterogeneity results in each location having different characteristics and allows the relationships between ...
Lilis Laome   +2 more
doaj   +1 more source

Double Penalized Expectile Regression for Linear Mixed Effects Model

open access: yesSymmetry, 2022
This paper constructs the double penalized expectile regression for linear mixed effects model, which can estimate coefficient and choose variable for random and fixed effects simultaneously. The method based on the linear mixed effects model by cojoining double penalized expectile regression.
Sihan Gao   +4 more
openaire   +1 more source

partR2: partitioning R2 in generalized linear mixed models

open access: yesbioRxiv, 2020
The coefficient of determination R2 quantifies the amount of variance explained by regression coefficients in a linear model. It can be seen as the fixed-effects complement to the repeatability R (intra-class correlation) for the variance explained by ...
M. Stoffel, S. Nakagawa, H. Schielzeth
semanticscholar   +1 more source

Primerjava različnih regresijskih modelov za napovedovanje debelinskega priraščanja jelke

open access: yesActa Silvae et Ligni, 2021
We present seven alternative statistical models for modelling tree diameter increment with data from permanent sampling plots. In addition to the polynomial regression model, we present a regression model with added random noise, a mixed linear model ...
Andrej Ficko, Vasilije Trifković
doaj   +1 more source

Analysis of neonatal clinical trials with twin births

open access: yesBMC Medical Research Methodology, 2009
Background In neonatal trials of pre-term or low-birth-weight infants, twins may represent 10–20% of the study sample. Mixed-effects models and generalized estimating equations are common approaches for handling correlated continuous or binary data ...
Shaffer Michele L   +2 more
doaj   +1 more source

On the estimation of variance parameters in non-standard generalised linear mixed models: application to penalised smoothing [PDF]

open access: yesStatistics and computing, 2018
We present a novel method for the estimation of variance parameters in generalised linear mixed models. The method has its roots in Harville (J Am Stat Assoc 72(358):320–338, 1977)’s work, but it is able to deal with models that have a precision matrix ...
M. Rodríguez-Álvarez   +3 more
semanticscholar   +1 more source

Longitudinal beta regression models for analyzing health-related quality of life scores over time

open access: yesBMC Medical Research Methodology, 2012
Background Health-related quality of life (HRQL) has become an increasingly important outcome parameter in clinical trials and epidemiological research. HRQL scores are typically bounded at both ends of the scale and often highly skewed.
Hunger Matthias   +2 more
doaj   +1 more source

Assessment of factors affecting flicker ERGs recorded with RETeval from data obtained from health checkup screening.

open access: yesPLoS ONE, 2023
PurposeTo determine the factors significantly associated with the amplitudes and implicit times of the flicker electroretinograms (ERGs) recorded with the RETeval system by analyzing the comprehensive data obtained during a health checkup screening ...
Taiga Inooka   +11 more
doaj   +2 more sources

MCMC methods for multi-response generalized linear mixed models

open access: yes, 2010
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form.
J. Hadfield
semanticscholar   +1 more source

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