Results 21 to 30 of about 604,873 (258)

Fast and flexible linear mixed models for genome-wide genetics. [PDF]

PLoS Genetics, 2019
Linear mixed effect models are powerful tools used to account for population structure in genome-wide association studies (GWASs) and estimate the genetic architecture of complex traits.
Daniel E Runcie, Lorin Crawford
doaj   +1 more source

Accessible analysis of longitudinal data with linear mixed effects models

Disease Models & Mechanisms, 2022
Longitudinal studies are commonly used to examine possible causal factors associated with human health and disease. However, the statistical models, such as two-way ANOVA, often applied in these studies do not appropriately model the experimental design,
Jessica I. Murphy, Nicholas E. Weaver, Audrey E. Hendricks   +2 more
doaj   +1 more source

Admissibility of Continuous Unbiased Estimators in Linear Mixed Models [PDF]

The Egyptian Statistical Journal, 1991
For a given linear function of the fixed effects in the usual mixed linear model, within the class of estimators, a discontinuous unbiased estimator is introduced.
Samia El-arishy
doaj   +1 more source

Modified BIC Criterion for Model Selection in Linear Mixed Models

Mathematics, 2023
Linear mixed-effects models are widely used in applications to analyze clustered, hierarchical, and longitudinal data. Model selection in linear mixed models is more challenging than that of linear models as the parameter vector in a linear mixed model ...
Hang Lai, Xin Gao
doaj   +1 more source

lmerTest Package: Tests in Linear Mixed Effects Models

Journal of Statistical Software, 2017
One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer?
Alexandra Kuznetsova, Per B. Brockhoff, Rune H. B. Christensen   +2 more
doaj   +1 more source

Implementation of generalized estimating equations and mixed linear models in Python [PDF]

Yixue xinzhi zazhi, 2022
Objective Explore the implementation of generalized estimation equations (GEE) and mixed linear models (MLM) in longitudinal data analysis using Python software, and expand its application in statistical analysis.Methods GEE and MLM were constructed by ...
Kui-Zhuang JIAO, Xu-Xi MA, Xiao-Qian MA, Chao-Yi LIU, Qing ZHANG, Lu MA   +5 more
doaj   +1 more source

Violation of the Sphericity Assumption and Its Effect on Type-I Error Rates in Repeated Measures ANOVA and Multi-Level Linear Models (MLM)

Frontiers in Psychology, 2017
We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach.
Nicolas Haverkamp, André Beauducel
doaj   +1 more source

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

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

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