Results 21 to 30 of about 1,319,586 (359)

Rates of Glaucoma Progression Derived from Linear Mixed Models Using Varied Random Effect Distributions

medRxiv, 2021
Purpose: To compare the ability of linear mixed models with different random effect distributions to estimate rates of visual field loss in glaucoma patients. Design: Retrospective cohort study.
S. Swaminathan, S. Berchuck, A. Jammal, J. Rao, F. Medeiros   +4 more
semanticscholar   +1 more source

Statistical analysis of comparative tumor growth repeated measures experiments in the ovarian cancer patient derived xenograft (PDX) setting

Scientific Reports, 2021
Repeated measures studies are frequently performed in patient-derived xenograft (PDX) models to evaluate drug activity or compare effectiveness of cancer treatment regimens. Linear mixed effects regression models were used to perform statistical modeling
Ann L. Oberg, Ethan P. Heinzen, Xiaonan Hou, Mariam M. Al Hilli, Rachel M. Hurley, Andrea E. Wahner Hendrickson, Krista M. Goergen, Melissa C. Larson, Marc A. Becker, Jeanette E. Eckel-Passow, Matthew J. Maurer, Scott H. Kaufmann, Paul Haluska, S. John Weroha   +13 more
doaj   +1 more source

Using Airborne Lidar, Multispectral Imagery, and Field Inventory Data to Estimate Basal Area, Volume, and Aboveground Biomass in Heterogeneous Mixed Species Forests: A Case Study in Southern Alabama

Remote Sensing, 2022
Airborne light detection and ranging (lidar) has proven to be a useful data source for estimating forest inventory metrics such as basal area (BA), volume, and aboveground biomass (AGB) and for producing wall-to-wall maps for validation of satellite ...
Schyler Brown, Lana L. Narine, John Gilbert   +2 more
doaj   +1 more source

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

Functional 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, Rodrigo Silva Alves   +1 more
semanticscholar   +1 more source

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

Mathematics, 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, I Nyoman Budiantara, Vita Ratnasari   +2 more
doaj   +1 more source

Two penalized mixed–integer nonlinear programming approaches to tackle multicollinearity and outliers effects in linear regression models

Journal of Industrial and Management Optimization, 2020
In classical regression analysis, the ordinary least–squares estimation is the best strategy when the essential assumptions such as normality and independency to the error terms as well as ignorable multicollinearity in the covariates are met.
M. Roozbeh, S. Babaie-Kafaki, Z. Aminifard   +2 more
semanticscholar   +1 more source

Primerjava različnih regresijskih modelov za napovedovanje debelinskega priraščanja jelke

Acta 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

partR2: partitioning R2 in generalized linear mixed models

bioRxiv, 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

Double Penalized Expectile Regression for Linear Mixed Effects Model

Symmetry, 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, Jiaqing Chen, Zihao Yuan, Jie Liu, Yangxin Huang   +4 more
openaire   +1 more source

Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting [PDF]

, 2011
With the emergence of semi- and nonparametric regression the generalized linear mixed model has been expanded to account for additive predictors. In the present paper an approach to variable selection is proposed that works for generalized additive mixed
Groll, Andreas, Tutz, Gerhard
core   +4 more sources