Results 51 to 60 of about 1,394,927 (329)
Sparse Probit Linear Mixed Model
, 2017 Linear Mixed Models (LMMs) are important tools in statistical genetics. When used for feature selection, they allow to find a sparse set of genetic traits that best predict a continuous phenotype of interest, while simultaneously correcting for various ...
Cunningham, John P. +5 more
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A mixed-effects model for growth curves analysis in a two-way crossed classification layout
Revista de Matemática: Teoría y Aplicaciones, 2009 We propose a mixed-effects linear model for analyzing growth curves data obtained using a two-way classification experiment. The model combines an unconstrained means model and a regression model on the time, in which the coefficients are considered ...
Mario Miguel Ojeda, Hardeo Sahai
doaj +1 more source
A comparison of multiple imputation methods for missing data in longitudinal studies
BMC Medical Research Methodology, 2018 Background Multiple imputation (MI) is now widely used to handle missing data in longitudinal studies. Several MI techniques have been proposed to impute incomplete longitudinal covariates, including standard fully conditional specification (FCS-Standard)
Md Hamidul Huque +3 more
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Imputation by PLS regression for linear mixed models [PDF]
, 2011 The problem of handling missing data for a linear mixed model in presence of correlation between covariates is considered. The missing mechanism concerns both dependent variable and design matrix.
Guyon, Emilie, Pommeret, Denys
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FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source
Adaptive Partially Linear Regression Models by Mixing Different Estimates [PDF]
American Journal of Theoretical and Applied Statistics, 2019 This paper proposes adapting the semiparametric partial model (PLM) by mixing different estimation procedures defined under different conditions. Choosing an estimation method of PLM, from several estimation methods, is an important issue, which depends on the performance of the method and the properties of the resulting estimators.
openaire +1 more source
Tau acetylation at K331 has limited impact on tau pathology in vivo
FEBS Letters, EarlyView.We mapped tau post‐translational modifications in humanized MAPT knock‐in mice and in amyloid‐bearing double knock‐in mice. Acetylation within the repeat domain, particularly around K331, showed modest increases under amyloid pathology. To test functional relevance, we generated MAPTK331Q knock‐in mice.
Shoko Hashimoto +3 more
wiley +1 more source
Developmental Cognitive NeuroscienceLinear mixed effects models (LMEs) have advantages for analyzing mean amplitude event-related potential (ERP) data. Compared to ANOVA and linear regression, LMEs retain more subjects and yield unbiased parameter estimates by accounting for trial-level ...
Megan J. Heise +2 more
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Fence methods for mixed model selection
, 2008 Many model search strategies involve trading off model fit with model complexity in a penalized goodness of fit measure. Asymptotic properties for these types of procedures in settings like linear regression and ARMA time series have been studied, but ...
Gu, Zhonghua +3 more
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Perturbation selection and influence measures in local influence analysis [PDF]
, 2007 Cook's [J. Roy. Statist. Soc. Ser. B 48 (1986) 133--169] local influence approach based on normal curvature is an important diagnostic tool for assessing local influence of minor perturbations to a statistical model.
Ibrahim, Joseph G. +3 more
core +3 more sources