<p>LME-RSI: a linear mixed-effects model with random slope and intercept; LME-RI: a linear mixed-effects model with only a random intercept term; GEE-Robust: GEE with the sandwich covariance estimator; GEE-Naive: GEE with the model-based covariance estimator; Baseline: a linear model at the baseline testing for the main effects of an SNP.</p
This paper focuses on the multivariate linear mixed-effects model, including all the correlations be...
Background Self-contained tests estimate and test the association between a phenotype and mean expre...
BACKGROUND: Linear mixed effects models (LMMs) are a common approach for analyzing longitudinal data...
<p>Simulation results at significance level with different methods for phenotypic data generated fr...
When (meta-)analyzing single-case experimental design (SCED) studies by means of hierarchical or mul...
Both fixed and random effects models have been used to simulate the meta-analyses. The fixed effects...
Use of mixed models is advocated almost ubiquitously when regression analysis is applied in data set...
Linear mixed effect (LME) models have become popular in modeling data in a wide variety of fields, p...
<p>The proportion of simulated traits for which the -log10(p) value of the causal SNP is above the t...
<p>Fixed effects for each model are in boldface, random effects and residuals are italicized and cov...
<p>*. The simulation model consists of 5 covariates, each with OR of 1.5. In analysis, we assume tha...
<p>The first to third columns denote the effect sizes of SNP1, SNP2 and interaction in pure samples ...
Background Self-contained tests estimate and test the association between a phenotype and mean expre...
University of Minnesota Ph.D. dissertation. February 2013. Major: Educational Psychology. Advisor: M...
<p>In all models, block was included as a random effect.</p><p>Statistical results from the generali...
This paper focuses on the multivariate linear mixed-effects model, including all the correlations be...
Background Self-contained tests estimate and test the association between a phenotype and mean expre...
BACKGROUND: Linear mixed effects models (LMMs) are a common approach for analyzing longitudinal data...
<p>Simulation results at significance level with different methods for phenotypic data generated fr...
When (meta-)analyzing single-case experimental design (SCED) studies by means of hierarchical or mul...
Both fixed and random effects models have been used to simulate the meta-analyses. The fixed effects...
Use of mixed models is advocated almost ubiquitously when regression analysis is applied in data set...
Linear mixed effect (LME) models have become popular in modeling data in a wide variety of fields, p...
<p>The proportion of simulated traits for which the -log10(p) value of the causal SNP is above the t...
<p>Fixed effects for each model are in boldface, random effects and residuals are italicized and cov...
<p>*. The simulation model consists of 5 covariates, each with OR of 1.5. In analysis, we assume tha...
<p>The first to third columns denote the effect sizes of SNP1, SNP2 and interaction in pure samples ...
Background Self-contained tests estimate and test the association between a phenotype and mean expre...
University of Minnesota Ph.D. dissertation. February 2013. Major: Educational Psychology. Advisor: M...
<p>In all models, block was included as a random effect.</p><p>Statistical results from the generali...
This paper focuses on the multivariate linear mixed-effects model, including all the correlations be...
Background Self-contained tests estimate and test the association between a phenotype and mean expre...
BACKGROUND: Linear mixed effects models (LMMs) are a common approach for analyzing longitudinal data...