Plotting Regression results from lme4 in R using Lattice (or something else)

linear-regression, lme4, r

Solution

Instead of using `lmList`, I'd recommend the more general plyr package.

library(plyr)

d <- data.frame(
 state = rep(c('NY', 'CA'), c(10, 10)), 
 year = rep(1:10, 2), 
 response = c(rnorm(10), rnorm(10))
)

# Create a list of models
# dlply = data frame -> list
models <- dlply(d, ~ state, function(df) { 
  lm(response ~ year, data = df)
})

# Extract the coefficients in a useful form
# ldply = list -> data frame
ldply(models, coef)

# We can get the predictions in a similar way, but we need
# to cast to a data frame so the numbers come out as rows,
# not columns.
predictions <- ldply(models, as.data.frame(predict))

`predictions` is a regular R data frame and so is easy to plot.

Problem

I have fit a regression using lme4 thanks to a previous answer. Now that I have a regression fit for each state I'd like to use lattice to plot QQ plots for each state. I would also like to plot error plots for each state in a lattice format. How do I make a lattice plot using the results of a lme4 regression? Below is a simple sample (yeah, I like a good alliteration) using two states. I would like to make a two panel lattice made from the object fits. ``` library(lme4) d <- data.frame(state=rep(c('NY', 'CA'), c(10, 10)), year=rep(1:10, 2), response=c(rnorm(10), rnorm(10))) fits <- lmList(response ~ year | state, data=d) ```

Original source