Mixed model

Known as: Mixed, Mixed linear model, Mixed models 
A mixed model is a statistical model containing both fixed effects and random effects. These models are useful in a wide variety of disciplines in… (More)
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Papers overview

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Highly Cited
2015
Highly Cited
2015
The analysis of experimental data with mixed-effects models requires decisions about the specification of the appropriate random… (More)
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Highly Cited
2014
Highly Cited
2014
Mon, 03 Dec 2018 17:38:00 GMT fitting linear mixed effects models pdf Fitting Linear Mixed-Effects Models Using lme4 Douglas… (More)
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Highly Cited
2010
Highly Cited
2010
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response… (More)
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Highly Cited
2007
Highly Cited
2007
This paper provides a non-technical introduction to mixed-effects models for the analysis of repeated measurement data with… (More)
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Highly Cited
2007
Highly Cited
2007
  • 2007
The paper by Austin et al. refers repeatedly to generalized linear mixed models, or GLMMs. Example. Suppose we are doing a simple… (More)
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Highly Cited
2006
Highly Cited
2006
UNLABELLED RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel… (More)
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Highly Cited
2006
Highly Cited
2006
Linear Mixed Models: A Practical Guide Using Statistical Software by Brady T. West, Kathleen B. Welch, and Andrzej T. Galecki… (More)
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Highly Cited
2003
Highly Cited
2003
MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under… (More)
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Highly Cited
2001
Highly Cited
2001
The determination of a list of differentially expressed genes is a basic objective in many cDNA microarray experiments. We… (More)
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Highly Cited
2001
Highly Cited
2001
Make more knowledge even in less time every day. You may not always spend your time and money to go abroad and get the experience… (More)
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