Contents
How to extract random effect from lme4 model?
Also checked any extractor functions in the lme4 package to no avail. Please help! …In general, you can look at the source of the print and summary methods for “mer” objects:
Is it worth it to use lme4 for regression?
In this article, we will look an example that could be analyzed with either a traditional regression approach, using lm (), or a more sophisticated approach using random effects via the lme4 package by Douglas Bates, Martin Maechler and Ben Bolker (2011). And then I’ll pose the question, “is it worth it?”
Which is the main function of the lme4 package?
The flagship function of the lme4 package is the lmer () function, a likelihood based system for estimating random effects models. Its formula notation works like lm ()’s for fixed effects, but if you try to run a basic lm () model in it, you’ll get an error message – lmer () needs random effects!
How to calculate the variance of random effects?
I take it that the variance of the varying state intercepts / random effects is 0.0063695. But when I extract the vector of these state random effects and calculate the variance
How does a linear mixed model ( LMM ) work?
Linear Mixed Model (LMM) also known as Linear Mixed Effects Model is one of key techniques in traditional Frequentist statistics. Here I will attempt to derive LMM solution from scratch from the Maximum Likelihood principal by optimizing mean and variance parameters of Fixed and Random Effects.
Why do you use LME instead of lmer?
because you don’t need any of the stuff that lmer offers (higher speed, handling of crossed random effects, GLMMs …). lme should give you exactly the same coefficient and variance estimates but will also compute df and p-values for you (which do make sense in a “classical” design such as you appear to have).
Can you use LME function in nlme R?
By default, lme4 R package and lmer R function do not provide measures of statistical significance such as p-values, however if you still would like to have a p-value of your LMM fit, it is possible to use lme function from the nlme R package:
How can I get p values from lmer?
You could use the package lmerTest. You just install/load it and the lmer models get extended. So e.g. would give you results with p-values. If p-values are the right indication is a little bit disputed, but if you want to have them, this is the way to get them.
Which is the best accessor method for lme4?
Some of the other answers are workable, but I claim that the best answer is to use the accessor method that is designed for this — VarCorr (this is the same as in lme4 ‘s predecessor, the nlme package).