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Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies
Efficient Algorithms Multivariate Linear Mixed Models Genome-wide Association Studies
2013/6/17
Multivariate linear mixed models (mvLMMs) have been widely used in many areas of genetics, and have attracted considerable recent interest in genome-wide association studies (GWASs). However, existing...
A stochastic variational framework for fitting and diagnosing generalized linear mixed models
Hierarchical model Identify divergent units Large longitudinal data Non-conjugate model Stochastic approximation Variational Bayes
2012/9/17
Variational Bayes computational methods are attracting increasing in-terest because of their ability to scale to large data sets. Here, application of the
non-conjugate variational message passing (N...
spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R
MCMC P-splines spike-and-slab prior normal-inverse-gamma
2011/6/20
The R package spikeSlabGAM implements Bayesian variable selection, model choice,
and regularized estimation in (geo-)additive mixed models for Gaussian, binomial, and
Poisson responses. Its purpose ...
Ridge parameter for g-prior distribution in probit mixed models with collinearity
Ridge parameter for g probit mixed models with collinearity g-prior of Zellner
2011/3/18
In the Bayesian variable selection framework, a common prior distribution for the regression coefficients is the g-prior of Zellner (1986). However, there are two standard cases in which the associate...
Mixed models for longitudinal left-censored repeated measures
Mixed model Repeated measures Left-censoring SAS proc NLMIXED HIV infection
2010/4/29
Longitudinal studies could be complicated by left-censored repeated measures. For example, in Human Immunodeficiency Virus infection, there is a detection limit of the assay used to quantify the plasm...
Bivariate linear mixed models using SAS proc MIXED
Bivariate random effects model Bivariate First Order Auto-regressive process SAS proc MIXED HIV infection
2010/4/29
Bivariate linear mixed models are useful when analyzing longitudinal data of two associated markers. In this paper, we present a bivariate linear mixed model including random effects or first-order au...
Admissible estimators of variance components in normal mixed models
Admissible estimators variance components normal mixed models
2009/9/23
A sulficient condition for an invariant quadratic
estimator of a linear function of the vector of variance components to
be admissible under the mean square &or among all translation
invariant esti...
A Default Conjugate Prior for Variance Components in Generalized Linear Mixed Models(Comment on Article by Browne and Draper)
Choice of prior hierarchical models noninformative priors random effects
2009/9/21
For a scalar random-eect variance, Browne and Draper (2005) have found that the uniform prior works well. It would be valuable to know more about the vector case, in which a second-stage prior on the ...
Testing polynomial covariate effects in linear and generalized linear mixed models
Likelihood Ratio Test Restricted Maximum Likelihood （REML） Score Test
2009/2/11
An important feature of linear mixed models and generalized linear mixed models is that the conditional mean of the response given the random effects, after transformed by a link function, is linearly...