Results 41 to 50 of about 3,822,020 (321)

A Kenward-Roger approximation and parametric bootstrap methods for tests in linear mixed models: The R Package pbkrtest

, 2014
When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic ?2 test. Such tests can, however, be very poor for small and moderate sample sizes.
U. Halekoh, Søren Højsgaard
semanticscholar   +1 more source

MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits

Genome Biology, 2020
Large-scale phenotype data can enhance the power of genomic prediction in plant and animal breeding, as well as human genetics. However, the statistical foundation of multi-trait genomic prediction is based on the multivariate linear mixed effect model ...
D. Runcie, J. Qu, Hao Cheng, Lorin Crawford   +3 more
semanticscholar   +1 more source

Using linear mixed models to analyze learning processes within sessions improves detection of treatment effects: An exemplary study of chronometric mental rotation

Methods in Psychology, 2022
Practice effects occur for many cognitive tasks. They are observed not only between repeated tests, but also within sessions. They can confound the detection of treatment effects, even when compared with control groups.
Leonardo Jost, Petra Jansen
doaj   +1 more source

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence [PDF]

, 2015
A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context.
Aas K, Aristidis K Nikoloulopoulos, Brenner H, Chu H, Chu H, Demidenko E, Genest C, Genest C, Genest C, Hamza TH, Hoyer A, Hua L, Hult H, Joe H, Joe H, Joe H, Joe H, Joe H, Karageorgopoulos DE, Kurowicka D, Kuss O, Leeflang MMG, Leeflang MMG, Ma X, Mavridis D, McNeil AJ, Nash JC, Nelsen RB, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Panagiotelis A, Paul M, Serfling RJ, Shen C, Stroud AH, Vuong QH, Ye Y   +41 more
core   +2 more sources

Fiducial Inference in Linear Mixed-Effects Models

Entropy
We 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, Xinmin Li, Hongwei Gao, Chenchen Zou   +3 more
doaj   +1 more source

Application of an Empirical Best Linear Unbiased Prediction Fay–Herriot (EBLUP-FH) Multivariate Method with Cluster Information to Estimate Average Household Expenditure

Mathematics, 2022
Data at a smaller regional level has now become a necessity for local governments. The average data on household expenditure on food and non-food is designed for provincial and district/city estimation levels.
Armalia Desiyanti, Irlandia Ginanjar, Toni Toharudin   +2 more
doaj   +1 more source

Linear Mixed Models: Part I

, 2021
The best way to understand a linear mixed model, or mixed linear model in some earlier literature, is to first recall a linear regression model. The latter can be expressed as y = Xβ + 𝜖, where y is a vector of observations, X is a matrix of known covariates, β is a vector of unknown regression coefficients, and 𝜖 is a vector of (unobservable random ...
Jiming Jiang, Thuan Nguyen
openaire   +1 more source

Variational approximation for mixtures of linear mixed models

, 2012
Mixtures of linear mixed models (MLMMs) are useful for clustering grouped data and can be estimated by likelihood maximization through the EM algorithm.
Armagan A., Attias H., Booth J.G., Corduneanu A., David J. Nott, Dempster A.P., Meng X.L., Papaspiliopoulos O., Sahu S.K., Scharl T., Siew Li Tan, Verbeek J.J., Wang B., Waterhouse S., Winn J., Wu B., Yeung K.Y., ———   +17 more
core   +2 more sources

Linear mixed effects models under inequality constraints with applications.

PLoS ONE, 2014
Constraints arise naturally in many scientific experiments/studies such as in, epidemiology, biology, toxicology, etc. and often researchers ignore such information when analyzing their data and use standard methods such as the analysis of variance ...
Laura Farnan, Anastasia Ivanova, Shyamal D Peddada   +2 more
doaj   +1 more source

Psychosocial Outcomes in Patients With Endocrine Tumor Syndromes: A Systematic Review

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction The combination of disease manifestations, the familial burden, and varying penetrance of endocrine tumor syndromes (ETSs) is unique. This review aimed to portray and summarize available data on psychosocial outcomes in patients with ETSs and explore gaps and opportunities for future research and care.
Daniël Zwerus, Floortje Strobbe, Annemarie A. Verrijn Stuart, Hanneke M. van Santen, Gerlof D. Valk, Sasja A. Schepers, Rachel S. van Leeuwaarde   +6 more
wiley   +1 more source