lme4

Surviving a binomial mixed model

November 11, 2011 | Luis

A few years ago we had this really cool idea: we had to establish a trial to understand wood quality in context. Sort of following the saying “we don’t know who discovered water, but we are sure that it wasn’t … Continue reading → [Read more...]

Covariance structures

October 26, 2011 | Luis

In most mixed linear model packages (e.g. asreml, lme4, nlme, etc) one needs to specify only the model equation (the bit that looks like y ~ factors...) when fitting simple models. We explicitly say nothing about the covariances that complete … Continue reading → [Read more...]

Large applications of linear mixed models

October 18, 2011 | Luis

In a previous post I summarily described our options for (generalized to varying degrees) linear mixed models from a frequentist point of view: nlme, lme4 and ASReml-R†, followed by a quick example for a split-plot experiment. But who is really … Continue reading → [Read more...]

Linear mixed models in R

October 16, 2011 | Luis

A substantial part of my job has little to do with statistics; nevertheless, a large proportion of the statistical side of things relates to applications of linear mixed models. The bulk of my use of mixed models relates to the … Continue reading → [Read more...]

GLMM Hell

July 7, 2011 | Daniel Hocking

I have been starting to analyze some data I have of repeated counts of salamanders from 5 plots over 4 years. I am trying to develop a predictive model of salamander nighttime surface activity as a function of weather variables. The repeated counting l...
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lme4 stands 4 Linear mixed-effects…

February 19, 2010 | Manos Parzakonis

There is a certain hype about mixed (and random) effects among statistician and analysts. You can show some love to Douglas Bates and Martin Maechler for maintaing the lme4 package for our cupid, R I copy the entity of the information of the projects page. Doxygen documentation of the underlying ... [Read more...]

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